{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://deecamp.chuangxin.com/assets/image/logo_nav_zh.jpg\" width=\"40%\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "block_1.attributes  block_2.attributes\tblock_3.attributes\r\n",
      "block_1.tuples\t    block_2.tuples\tblock_3.tuples\r\n"
     ]
    }
   ],
   "source": [
    "! ls /data/jupyter_root/ZJ/test1.0 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 定义一个函数，先输出原始feature文件的P & R，再输出通过D-Cube分块的P & R"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "名称 | 定义\n",
    " --- | ---\n",
    "TP\t| 真实类别为positive，模型预测的类别也为positive\n",
    "FP\t| 预测为positive，但真实类别为negative，真实类别和预测类别不一致\n",
    "FN\t| 预测为negative，但真实类别为positive，真实类别和预测类别不一致\n",
    "TN\t| 真实类别为negative，模型预测的类别也为negative"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "准确率（accuracy）计算公式如下所示 不计算这个\n",
    "\n",
    "\\begin{equation}\\label{equ:accuracy} \\mbox{accuracy} = \\frac{TP+TN}{TP+TN+FP+FN} = \\frac{TP+TN }{\\mbox{all data}} \\end{equation}\n",
    "\n",
    "positive class的精确率（precision）计算公式如下\n",
    "\n",
    "\\begin{equation}\\label{equ:precision} \\mbox{precision} = \\frac{TP}{TP+FP} = \\frac{TP}{\\mbox{预测为positive的样本}} \\end{equation}\n",
    "\n",
    "positive class的召回率（recall）计算公式如下\n",
    "\n",
    "\\begin{equation}\\label{equ:recall} \\mbox{recall} = \\frac{TP}{TP+FN} = \\frac{TP}{\\mbox{真实为positive的样本}} \\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# 得到feature have name的PR（输入：f_count：第几个特征，j：无用，choice：第几个block）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_PR(f_count,j,choice):#f_count：the index of feature;j: index of test; choice: index of block\n",
    "    \n",
    "    #准备用于读取数据的 pandas头（防止第一行数据成为标签）\n",
    "    data_path=\"/data/jupyter_root/dcube_data/have_name/feature\"#feature文件位置\n",
    "    #try:\n",
    "    cols = pd.read_csv(data_path+str(f_count)+\"/block_1.tuples\",nrows=1).columns#先读第一行，用于提取数据维度\n",
    "    #except e:\n",
    "    #    print(e)\n",
    "    #    print(\"false1\")\n",
    "    #    return 0        \n",
    "\n",
    "    user_index=['user_name']#初始化一个等待补全的names\n",
    "    #print(cols.shape[0]-1)\n",
    "    for i in range(1,cols.shape[0]-1):\n",
    "            user_index.append(str(i))\n",
    "    user_index.append('count')#补上最后的count\n",
    "    \n",
    "    #开始读取数据\n",
    "    #result=pd.read_csv(data_path+str(f_count)+\"/test\"+str(j)+\"/block_1.tuples\",sep=',',names=user_index)#读取全部的数据，并给上names\n",
    "    #try:\n",
    "    if(choice=='all'):#读取blocks.txt\n",
    "        result=pd.read_csv(data_path+str(f_count)+\"/blocks.txt\",sep=',',names=user_index)\n",
    "    elif(choice==1 or choice==2 or choice==3 ):#读取block_choice.tuples\n",
    "        result=pd.read_csv(data_path+str(f_count)+\"/block_\"+str(choice)+\".tuples\",sep=',',names=user_index)\n",
    "    elif(choice==12 or choice==13 or choice==23 or choice ==123 ):#读取blockchoice.txt\n",
    "        result=pd.read_csv(data_path+str(f_count)+\"/block\"+str(choice)+\".txt\",sep=',',names=user_index)\n",
    "    #except:\n",
    "    #    print(\"false2\")\n",
    "    #    return 0\n",
    "    names = result['user_name'].drop_duplicates()#预测出坏用户的用户列表\n",
    "    #print(names)\n",
    "    dataset = pd.read_csv(open('/data/csv/label_eventsV1.csv','r',encoding = 'gb18030'))#读取总标签数据\n",
    "    data = dataset[dataset['user_name'].isin(names)][['user_name','label']]#预测出坏用户的真实标签分布\n",
    "    data = data.drop_duplicates()#去重\n",
    "    #print(data)\n",
    "\n",
    "    \n",
    "    raw_result=pd.read_csv(data_path+str(f_count)+\".txt\",sep=',',names=user_index)#读取全部的原始数据，并给上names\n",
    "    raw_names = raw_result['user_name'].drop_duplicates()#原始数据中用户的用户列表\n",
    "    #print(raw_names)\n",
    "    raw_data = dataset[dataset['user_name'].isin(raw_names)][['user_name','label']]#原始数据中坏用户的真实标签分布\n",
    "    raw_data = raw_data.drop_duplicates()#去重\n",
    "    #print(raw_data)\n",
    "    \n",
    "    \n",
    "    TP=data.label.sum()\n",
    "    if(TP==0):\n",
    "        return 0\n",
    "    P=raw_data.label.sum()\n",
    "    FP=data.label.count()-data.label.sum()\n",
    "    N=raw_data.label.count()-raw_data.label.sum()\n",
    "    Precision = (TP/P)/(TP/P+FP/N) #精确率计算\n",
    "\n",
    "    #data_label_1 = dataset[dataset['label']==1][['user_name','label']] #原数据中label为1的坏用户\n",
    "    #data_label_1 = data_label_1.drop_duplicates()#去重\n",
    "    Recall = data.label.sum()/raw_data.label.sum() # 召回率计算\n",
    "    print(\"TP\",TP,\"P\",P,\"FP\",FP,\"N\",N)\n",
    "    print('测试特征'+str(f_count)+\"_\"+str(j)+str(choice))\n",
    "    print('\\t\\t精确率 Precision\\t= '+str(Precision))\n",
    "    print('\\t\\t召回率 Recall   \\t= '+str(Recall))\n",
    "#get_PR(1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_no_name_PR(f_count,feature_user,find_user):\n",
    "    \n",
    "    dataset = pd.read_csv(open('/data/csv/label_eventsV1.csv','r',encoding = 'gb18030'))#读取总标签数据\n",
    "    data = dataset[dataset['user_name'].isin(find_user)][['user_name','label']]#预测出坏用户的真实标签分布\n",
    "    data = data.drop_duplicates()#去重\n",
    "    #print(data)\n",
    "\n",
    "    \n",
    "    #raw_result=pd.read_csv(data_path+str(f_count)+\".txt\",sep=',',names=user_index)#读取全部的原始数据，并给上names\n",
    "    #raw_names = raw_result['user_name'].drop_duplicates()#原始数据中用户的用户列表\n",
    "    #print(raw_names)\n",
    "    raw_data = dataset[dataset['user_name'].isin(feature_user)][['user_name','label']]#原始数据中坏用户的真实标签分布\n",
    "    raw_data = raw_data.drop_duplicates()#去重\n",
    "    #print(raw_data)\n",
    "    \n",
    "    \n",
    "    TP=data.label.sum()\n",
    "    #if(TP==0):\n",
    "        #return 0\n",
    "    P=raw_data.label.sum()\n",
    "    FP=data.label.count()-data.label.sum()\n",
    "    N=raw_data.label.count()-raw_data.label.sum()\n",
    "    Precision = (TP/P)/(TP/P+FP/N) #精确率计算\n",
    "\n",
    "    #data_label_1 = dataset[dataset['label']==1][['user_name','label']] #原数据中label为1的坏用户\n",
    "    #data_label_1 = data_label_1.drop_duplicates()#去重\n",
    "    Recall = data.label.sum()/raw_data.label.sum() # 召回率计算\n",
    "    print(\"TP\",TP,\"P\",P,\"FP\",FP,\"N\",N)\n",
    "    print('测试特征'+f_count)\n",
    "    print('\\t\\t精确率 Precision\\t= '+str(Precision))\n",
    "    print('\\t\\t召回率 Recall   \\t= '+str(Recall))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TP 5498 P 5538 FP 3855 N 3871\n",
      "测试特征feature0block_1\n",
      "\t\t精确率 Precision\t= 0.49922320801858744\n",
      "\t\t召回率 Recall   \t= 0.9927771758757674\n",
      "TP 4800 P 5538 FP 2608 N 3871\n",
      "测试特征feature0block_2\n",
      "\t\t精确率 Precision\t= 0.5626469844389083\n",
      "\t\t召回率 Recall   \t= 0.866738894907909\n",
      "TP 5538 P 5538 FP 3871 N 3871\n",
      "测试特征feature0block_3\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 803 P 5538 FP 478 N 3871\n",
      "测试特征feature1block_1\n",
      "\t\t精确率 Precision\t= 0.5400697445277858\n",
      "\t\t召回率 Recall   \t= 0.14499819429396893\n",
      "TP 780 P 5538 FP 480 N 3871\n",
      "测试特征feature1block_2\n",
      "\t\t精确率 Precision\t= 0.5318038192059349\n",
      "\t\t召回率 Recall   \t= 0.14084507042253522\n",
      "TP 734 P 5538 FP 501 N 3871\n",
      "测试特征feature1block_3\n",
      "\t\t精确率 Precision\t= 0.505945313373643\n",
      "\t\t召回率 Recall   \t= 0.13253882267966774\n",
      "TP 115 P 5538 FP 67 N 3871\n",
      "测试特征feature2block_1\n",
      "\t\t精确率 Precision\t= 0.5454043133454463\n",
      "\t\t召回率 Recall   \t= 0.02076561935716865\n",
      "TP 107 P 5538 FP 53 N 3871\n",
      "测试特征feature2block_2\n",
      "\t\t精确率 Precision\t= 0.5852629109905032\n",
      "\t\t召回率 Recall   \t= 0.01932105453232214\n",
      "TP 93 P 5538 FP 66 N 3871\n",
      "测试特征feature2block_3\n",
      "\t\t精确率 Precision\t= 0.4962061223055198\n",
      "\t\t召回率 Recall   \t= 0.016793066088840736\n",
      "TP 248 P 5538 FP 130 N 3871\n",
      "测试特征feature3block_1\n",
      "\t\t精确率 Precision\t= 0.5714510211030341\n",
      "\t\t召回率 Recall   \t= 0.04478150957024196\n",
      "TP 243 P 5538 FP 129 N 3871\n",
      "测试特征feature3block_2\n",
      "\t\t精确率 Precision\t= 0.5683515049348814\n",
      "\t\t召回率 Recall   \t= 0.043878656554712896\n",
      "TP 221 P 5538 FP 148 N 3871\n",
      "测试特征feature3block_3\n",
      "\t\t精确率 Precision\t= 0.510705832136898\n",
      "\t\t召回率 Recall   \t= 0.03990610328638498\n",
      "TP 372 P 5538 FP 232 N 3871\n",
      "测试特征feature4block_1\n",
      "\t\t精确率 Precision\t= 0.5284781277937544\n",
      "\t\t召回率 Recall   \t= 0.06717226435536294\n",
      "TP 335 P 5538 FP 228 N 3871\n",
      "测试特征feature4block_2\n",
      "\t\t精确率 Precision\t= 0.5066656924986589\n",
      "\t\t召回率 Recall   \t= 0.06049115204044782\n",
      "TP 358 P 5538 FP 201 N 3871\n",
      "测试特征feature4block_3\n",
      "\t\t精确率 Precision\t= 0.5545587837480932\n",
      "\t\t召回率 Recall   \t= 0.06464427591188154\n",
      "TP 5523 P 5538 FP 3716 N 3871\n",
      "测试特征feature5block_1\n",
      "\t\t精确率 Precision\t= 0.5095370473580225\n",
      "\t\t召回率 Recall   \t= 0.9972914409534128\n",
      "TP 38 P 5538 FP 430 N 3871\n",
      "测试特征feature5block_2\n",
      "\t\t精确率 Precision\t= 0.0581774202096314\n",
      "\t\t召回率 Recall   \t= 0.006861682918020947\n",
      "TP 151 P 5538 FP 750 N 3871\n",
      "测试特征feature5block_3\n",
      "\t\t精确率 Precision\t= 0.12336817418073917\n",
      "\t\t召回率 Recall   \t= 0.02726616106897797\n",
      "TP 5417 P 5538 FP 3609 N 3871\n",
      "测试特征feature6block_1\n",
      "\t\t精确率 Precision\t= 0.5119954173090149\n",
      "\t\t召回率 Recall   \t= 0.9781509570241964\n",
      "TP 708 P 5538 FP 567 N 3871\n",
      "测试特征feature6block_2\n",
      "\t\t精确率 Precision\t= 0.4660434090146197\n",
      "\t\t召回率 Recall   \t= 0.12784398699891658\n",
      "TP 38 P 5538 FP 416 N 3871\n",
      "测试特征feature6block_3\n",
      "\t\t精确率 Precision\t= 0.06001780566043741\n",
      "\t\t召回率 Recall   \t= 0.006861682918020947\n",
      "TP 5387 P 5538 FP 3592 N 3871\n",
      "测试特征feature7block_1\n",
      "\t\t精确率 Precision\t= 0.511787550514997\n",
      "\t\t召回率 Recall   \t= 0.972733838931022\n",
      "TP 868 P 5538 FP 694 N 3871\n",
      "测试特征feature7block_2\n",
      "\t\t精确率 Precision\t= 0.46645028736430016\n",
      "\t\t召回率 Recall   \t= 0.15673528349584687\n",
      "TP 39 P 5538 FP 428 N 3871\n",
      "测试特征feature7block_3\n",
      "\t\t精确率 Precision\t= 0.059879035376738284\n",
      "\t\t召回率 Recall   \t= 0.007042253521126761\n",
      "TP 5449 P 5538 FP 3637 N 3871\n",
      "测试特征feature8block_1\n",
      "\t\t精确率 Precision\t= 0.5115360489935864\n",
      "\t\t召回率 Recall   \t= 0.9839292163235825\n",
      "TP 5526 P 5538 FP 3784 N 3871\n",
      "测试特征feature8block_2\n",
      "\t\t精确率 Precision\t= 0.5051403244314855\n",
      "\t\t召回率 Recall   \t= 0.9978331527627302\n",
      "TP 90 P 5538 FP 363 N 3871\n",
      "测试特征feature8block_3\n",
      "\t\t精确率 Precision\t= 0.14770524580655994\n",
      "\t\t召回率 Recall   \t= 0.016251354279523293\n",
      "TP 5523 P 5538 FP 3720 N 3871\n",
      "测试特征feature9block_1\n",
      "\t\t精确率 Precision\t= 0.5092681806458953\n",
      "\t\t召回率 Recall   \t= 0.9972914409534128\n",
      "TP 187 P 5538 FP 838 N 3871\n",
      "测试特征feature9block_2\n",
      "\t\t精确率 Precision\t= 0.13493283248094354\n",
      "\t\t召回率 Recall   \t= 0.033766702780787285\n",
      "TP 202 P 5538 FP 903 N 3871\n",
      "测试特征feature9block_3\n",
      "\t\t精确率 Precision\t= 0.1352196080899834\n",
      "\t\t召回率 Recall   \t= 0.036475261827374504\n",
      "TP 5419 P 5538 FP 3616 N 3871\n",
      "测试特征feature10block_1\n",
      "\t\t精确率 Precision\t= 0.5116034914773314\n",
      "\t\t召回率 Recall   \t= 0.9785120982304081\n",
      "TP 5445 P 5538 FP 3782 N 3871\n",
      "测试特征feature10block_2\n",
      "\t\t精确率 Precision\t= 0.5015810529792138\n",
      "\t\t召回率 Recall   \t= 0.9832069339111592\n",
      "TP 8 P 5538 FP 38 N 3871\n",
      "测试特征feature10block_3\n",
      "\t\t精确率 Precision\t= 0.1282786274087452\n",
      "\t\t召回率 Recall   \t= 0.001444564824846515\n",
      "TP 5391 P 5538 FP 3600 N 3871\n",
      "测试特征feature11block_1\n",
      "\t\t精确率 Precision\t= 0.5114171395273284\n",
      "\t\t召回率 Recall   \t= 0.9734561213434453\n",
      "TP 5536 P 5538 FP 3859 N 3871\n",
      "测试特征feature11block_2\n",
      "\t\t精确率 Precision\t= 0.5006858952214152\n",
      "\t\t召回率 Recall   \t= 0.9996388587937883\n",
      "TP 22 P 5538 FP 87 N 3871\n",
      "测试特征feature11block_3\n",
      "\t\t精确率 Precision\t= 0.15020600809922255\n",
      "\t\t召回率 Recall   \t= 0.0039725532683279165\n",
      "TP 5449 P 5538 FP 3642 N 3871\n",
      "测试特征feature12block_1\n",
      "\t\t精确率 Precision\t= 0.5111927726099803\n",
      "\t\t召回率 Recall   \t= 0.9839292163235825\n",
      "TP 5491 P 5538 FP 3806 N 3871\n",
      "测试特征feature12block_2\n",
      "\t\t精确率 Precision\t= 0.5021027541706008\n",
      "\t\t召回率 Recall   \t= 0.9915131816540267\n",
      "TP 466 P 5538 FP 302 N 3871\n",
      "测试特征feature12block_3\n",
      "\t\t精确率 Precision\t= 0.5189005057586062\n",
      "\t\t召回率 Recall   \t= 0.0841459010473095\n",
      "TP 4800 P 4800 FP 2608 N 2608\n",
      "测试特征feature13block_1\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 4800 P 4800 FP 2608 N 2608\n",
      "测试特征feature13block_2\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 4800 P 4800 FP 2608 N 2608\n",
      "测试特征feature13block_3\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 4049 P 4800 FP 2104 N 2608\n",
      "测试特征feature14block_1\n",
      "\t\t精确率 Precision\t= 0.5111474945147372\n",
      "\t\t召回率 Recall   \t= 0.8435416666666666\n",
      "TP 1959 P 4800 FP 1193 N 2608\n",
      "测试特征feature14block_2\n",
      "\t\t精确率 Precision\t= 0.47151356212262835\n",
      "\t\t召回率 Recall   \t= 0.408125\n",
      "TP 653 P 4800 FP 398 N 2608\n",
      "测试特征feature14block_3\n",
      "\t\t精确率 Precision\t= 0.4713047790682743\n",
      "\t\t召回率 Recall   \t= 0.13604166666666667\n",
      "TP 4660 P 4800 FP 2502 N 2608\n",
      "测试特征feature15block_1\n",
      "\t\t精确率 Precision\t= 0.5029731555178852\n",
      "\t\t召回率 Recall   \t= 0.9708333333333333\n",
      "TP 592 P 4800 FP 369 N 2608\n",
      "测试特征feature15block_2\n",
      "\t\t精确率 Precision\t= 0.46572327651112955\n",
      "\t\t召回率 Recall   \t= 0.12333333333333334\n",
      "TP 136 P 4800 FP 129 N 2608\n",
      "测试特征feature15block_3\n",
      "\t\t精确率 Precision\t= 0.3641979365183676\n",
      "\t\t召回率 Recall   \t= 0.028333333333333332\n",
      "TP 4692 P 4800 FP 2531 N 2608\n",
      "测试特征feature16block_1\n",
      "\t\t精确率 Precision\t= 0.5018030360292265\n",
      "\t\t召回率 Recall   \t= 0.9775\n",
      "TP 551 P 4800 FP 361 N 2608\n",
      "测试特征feature16block_2\n",
      "\t\t精确率 Precision\t= 0.4533422844538218\n",
      "\t\t召回率 Recall   \t= 0.11479166666666667\n",
      "TP 4800 P 4800 FP 2608 N 2608\n",
      "测试特征feature16block_3\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 4285 P 4800 FP 2294 N 2608\n",
      "测试特征feature17block_1\n",
      "\t\t精确率 Precision\t= 0.5036977474570099\n",
      "\t\t召回率 Recall   \t= 0.8927083333333333\n",
      "TP 2033 P 4800 FP 1131 N 2608\n",
      "测试特征feature17block_2\n",
      "\t\t精确率 Precision\t= 0.49409479050335553\n",
      "\t\t召回率 Recall   \t= 0.42354166666666665\n",
      "TP 853 P 4800 FP 509 N 2608\n",
      "测试特征feature17block_3\n",
      "\t\t精确率 Precision\t= 0.47658694929371803\n",
      "\t\t召回率 Recall   \t= 0.17770833333333333\n",
      "TP 4245 P 4800 FP 2264 N 2608\n",
      "测试特征feature18block_1\n",
      "\t\t精确率 Precision\t= 0.5046439628482973\n",
      "\t\t召回率 Recall   \t= 0.884375\n",
      "TP 2001 P 4800 FP 1118 N 2608\n",
      "测试特征feature18block_2\n",
      "\t\t精确率 Precision\t= 0.49301880546523913\n",
      "\t\t召回率 Recall   \t= 0.416875\n",
      "TP 4152 P 4800 FP 2201 N 2608\n",
      "测试特征feature18block_3\n",
      "\t\t精确率 Precision\t= 0.5061612054961723\n",
      "\t\t召回率 Recall   \t= 0.865\n",
      "TP 3993 P 4800 FP 2124 N 2608\n",
      "测试特征feature19block_1\n",
      "\t\t精确率 Precision\t= 0.5053021639536699\n",
      "\t\t召回率 Recall   \t= 0.831875\n",
      "TP 4622 P 4800 FP 2496 N 2608\n",
      "测试特征feature19block_2\n",
      "\t\t精确率 Precision\t= 0.5015264421316667\n",
      "\t\t召回率 Recall   \t= 0.9629166666666666\n",
      "TP 4309 P 4800 FP 2296 N 2608\n",
      "测试特征feature19block_3\n",
      "\t\t精确率 Precision\t= 0.5048761219896677\n",
      "\t\t召回率 Recall   \t= 0.8977083333333333\n",
      "TP 4186 P 4800 FP 2232 N 2608\n",
      "测试特征feature20block_1\n",
      "\t\t精确率 Precision\t= 0.5047036876496946\n",
      "\t\t召回率 Recall   \t= 0.8720833333333333\n",
      "TP 4656 P 4800 FP 2525 N 2608\n",
      "测试特征feature20block_2\n",
      "\t\t精确率 Precision\t= 0.5004708433239164\n",
      "\t\t召回率 Recall   \t= 0.97\n",
      "TP 666 P 4800 FP 418 N 2608\n",
      "测试特征feature20block_3\n",
      "\t\t精确率 Precision\t= 0.4640063601159183\n",
      "\t\t召回率 Recall   \t= 0.13875\n",
      "TP 4266 P 4800 FP 2183 N 2608\n",
      "测试特征feature21block_1\n",
      "\t\t精确率 Precision\t= 0.5149815812977965\n",
      "\t\t召回率 Recall   \t= 0.88875\n",
      "TP 2179 P 4800 FP 1296 N 2608\n",
      "测试特征feature21block_2\n",
      "\t\t精确率 Precision\t= 0.47740319929245123\n",
      "\t\t召回率 Recall   \t= 0.45395833333333335\n",
      "TP 448 P 4800 FP 345 N 2608\n",
      "测试特征feature21block_3\n",
      "\t\t精确率 Precision\t= 0.4136774602886859\n",
      "\t\t召回率 Recall   \t= 0.09333333333333334\n",
      "TP 4219 P 4800 FP 2155 N 2608\n",
      "测试特征feature22block_1\n",
      "\t\t精确率 Precision\t= 0.5154388744690627\n",
      "\t\t召回率 Recall   \t= 0.8789583333333333\n",
      "TP 3472 P 4800 FP 1907 N 2608\n",
      "测试特征feature22block_2\n",
      "\t\t精确率 Precision\t= 0.49729182556615087\n",
      "\t\t召回率 Recall   \t= 0.7233333333333334\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TP 3855 P 4800 FP 2034 N 2608\n",
      "测试特征feature22block_3\n",
      "\t\t精确率 Precision\t= 0.5073330830436836\n",
      "\t\t召回率 Recall   \t= 0.803125\n",
      "TP 3690 P 4800 FP 1900 N 2608\n",
      "测试特征feature23block_1\n",
      "\t\t精确率 Precision\t= 0.5134318420446106\n",
      "\t\t召回率 Recall   \t= 0.76875\n",
      "TP 4496 P 4800 FP 2369 N 2608\n",
      "测试特征feature23block_2\n",
      "\t\t精确率 Precision\t= 0.5076713763588049\n",
      "\t\t召回率 Recall   \t= 0.9366666666666666\n",
      "TP 4068 P 4800 FP 2137 N 2608\n",
      "测试特征feature23block_3\n",
      "\t\t精确率 Precision\t= 0.5084282585892789\n",
      "\t\t召回率 Recall   \t= 0.8475\n",
      "TP 4404 P 4800 FP 2283 N 2608\n",
      "测试特征feature24block_1\n",
      "\t\t精确率 Precision\t= 0.5117454831645223\n",
      "\t\t召回率 Recall   \t= 0.9175\n",
      "TP 4560 P 4800 FP 2426 N 2608\n",
      "测试特征feature24block_2\n",
      "\t\t精确率 Precision\t= 0.505261440574272\n",
      "\t\t召回率 Recall   \t= 0.95\n",
      "TP 1388 P 4800 FP 819 N 2608\n",
      "测试特征feature24block_3\n",
      "\t\t精确率 Precision\t= 0.4793873849439764\n",
      "\t\t召回率 Recall   \t= 0.2891666666666667\n",
      "TP 5334 P 5484 FP 3734 N 3828\n",
      "测试特征feature25block_1\n",
      "\t\t精确率 Precision\t= 0.4992822736256978\n",
      "\t\t召回率 Recall   \t= 0.9726477024070022\n",
      "TP 192 P 5484 FP 131 N 3828\n",
      "测试特征feature25block_2\n",
      "\t\t精确率 Precision\t= 0.5057011930809562\n",
      "\t\t召回率 Recall   \t= 0.0350109409190372\n",
      "TP 142 P 5484 FP 84 N 3828\n",
      "测试特征feature25block_3\n",
      "\t\t精确率 Precision\t= 0.541285280692111\n",
      "\t\t召回率 Recall   \t= 0.025893508388037927\n",
      "TP 5225 P 5484 FP 3625 N 3828\n",
      "测试特征feature26block_1\n",
      "\t\t精确率 Precision\t= 0.5015270506108203\n",
      "\t\t召回率 Recall   \t= 0.9527716994894238\n",
      "TP 1519 P 5484 FP 1113 N 3828\n",
      "测试特征feature26block_2\n",
      "\t\t精确率 Precision\t= 0.48787759186952906\n",
      "\t\t召回率 Recall   \t= 0.27698760029175784\n",
      "TP 193 P 5484 FP 131 N 3828\n",
      "测试特征feature26block_3\n",
      "\t\t精确率 Precision\t= 0.5069996870728132\n",
      "\t\t召回率 Recall   \t= 0.035193289569657185\n",
      "TP 5195 P 5484 FP 3613 N 3828\n",
      "测试特征feature27block_1\n",
      "\t\t精确率 Precision\t= 0.5009164700427343\n",
      "\t\t召回率 Recall   \t= 0.9473012399708242\n",
      "TP 1196 P 5484 FP 938 N 3828\n",
      "测试特征feature27block_2\n",
      "\t\t精确率 Precision\t= 0.4709068243251583\n",
      "\t\t召回率 Recall   \t= 0.21808898614150254\n",
      "TP 176 P 5484 FP 122 N 3828\n",
      "测试特征feature27block_3\n",
      "\t\t精确率 Precision\t= 0.5017426584925557\n",
      "\t\t召回率 Recall   \t= 0.032093362509117436\n",
      "TP 5247 P 5484 FP 3644 N 3828\n",
      "测试特征feature28block_1\n",
      "\t\t精确率 Precision\t= 0.5012705515646277\n",
      "\t\t召回率 Recall   \t= 0.9567833698030634\n",
      "TP 1101 P 5484 FP 837 N 3828\n",
      "测试特征feature28block_2\n",
      "\t\t精确率 Precision\t= 0.47867738453486847\n",
      "\t\t召回率 Recall   \t= 0.20076586433260393\n",
      "TP 198 P 5484 FP 131 N 3828\n",
      "测试特征feature28block_3\n",
      "\t\t精确率 Precision\t= 0.5133911516796853\n",
      "\t\t召回率 Recall   \t= 0.036105032822757115\n",
      "TP 4287 P 5484 FP 2815 N 3828\n",
      "测试特征feature29block_1\n",
      "\t\t精确率 Precision\t= 0.5152784015722636\n",
      "\t\t召回率 Recall   \t= 0.7817286652078774\n",
      "TP 3375 P 5484 FP 2314 N 3828\n",
      "测试特征feature29block_2\n",
      "\t\t精确率 Precision\t= 0.5044812318690161\n",
      "\t\t召回率 Recall   \t= 0.6154266958424508\n",
      "TP 1545 P 5484 FP 1078 N 3828\n",
      "测试特征feature29block_3\n",
      "\t\t精确率 Precision\t= 0.5001060374367962\n",
      "\t\t召回率 Recall   \t= 0.2817286652078775\n",
      "TP 4175 P 5484 FP 2695 N 3828\n",
      "测试特征feature30block_1\n",
      "\t\t精确率 Precision\t= 0.5195460006865774\n",
      "\t\t召回率 Recall   \t= 0.7613056163384391\n",
      "TP 3896 P 5484 FP 2681 N 3828\n",
      "测试特征feature30block_2\n",
      "\t\t精确率 Precision\t= 0.5035669990895614\n",
      "\t\t召回率 Recall   \t= 0.7104303428154631\n",
      "TP 904 P 5484 FP 688 N 3828\n",
      "测试特征feature30block_3\n",
      "\t\t精确率 Precision\t= 0.47840050962852854\n",
      "\t\t召回率 Recall   \t= 0.1648431801604668\n",
      "TP 4140 P 5484 FP 2685 N 3828\n",
      "测试特征feature31block_1\n",
      "\t\t精确率 Precision\t= 0.518372417528717\n",
      "\t\t召回率 Recall   \t= 0.7549234135667396\n",
      "TP 4264 P 5484 FP 2960 N 3828\n",
      "测试特征feature31block_2\n",
      "\t\t精确率 Precision\t= 0.5013815290887806\n",
      "\t\t召回率 Recall   \t= 0.7775346462436178\n",
      "TP 803 P 5484 FP 591 N 3828\n",
      "测试特征feature31block_3\n",
      "\t\t精确率 Precision\t= 0.4867646947043577\n",
      "\t\t召回率 Recall   \t= 0.14642596644784828\n",
      "TP 4169 P 5484 FP 2713 N 3828\n",
      "测试特征feature32block_1\n",
      "\t\t精确率 Precision\t= 0.5175250374355191\n",
      "\t\t召回率 Recall   \t= 0.7602115244347192\n",
      "TP 3944 P 5484 FP 2699 N 3828\n",
      "测试特征feature32block_2\n",
      "\t\t精确率 Precision\t= 0.5049552914035638\n",
      "\t\t召回率 Recall   \t= 0.7191830780452224\n",
      "TP 837 P 5484 FP 595 N 3828\n",
      "测试特征feature32block_3\n",
      "\t\t精确率 Precision\t= 0.49544272041386633\n",
      "\t\t召回率 Recall   \t= 0.1526258205689278\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征feature33block_1\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征feature33block_2\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征feature33block_3\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 3966 P 5484 FP 2282 N 3828\n",
      "测试特征feature34block_1\n",
      "\t\t精确率 Precision\t= 0.5481536619139803\n",
      "\t\t召回率 Recall   \t= 0.7231947483588621\n",
      "TP 1991 P 5484 FP 1726 N 3828\n",
      "测试特征feature34block_2\n",
      "\t\t精确率 Precision\t= 0.44604543401940155\n",
      "\t\t召回率 Recall   \t= 0.36305616338439095\n",
      "TP 1192 P 5484 FP 1138 N 3828\n",
      "测试特征feature34block_3\n",
      "\t\t精确率 Precision\t= 0.4223504244074845\n",
      "\t\t召回率 Recall   \t= 0.21735959153902262\n",
      "TP 4932 P 5484 FP 3364 N 3828\n",
      "测试特征feature35block_1\n",
      "\t\t精确率 Precision\t= 0.5057801312649165\n",
      "\t\t召回率 Recall   \t= 0.899343544857768\n",
      "TP 1725 P 5484 FP 1308 N 3828\n",
      "测试特征feature35block_2\n",
      "\t\t精确率 Precision\t= 0.47932068036490305\n",
      "\t\t召回率 Recall   \t= 0.31455142231947486\n",
      "TP 556 P 5484 FP 518 N 3828\n",
      "测试特征feature35block_3\n",
      "\t\t精确率 Precision\t= 0.4283223453838537\n",
      "\t\t召回率 Recall   \t= 0.10138584974471189\n",
      "TP 5092 P 5484 FP 3492 N 3828\n",
      "测试特征feature36block_1\n",
      "\t\t精确率 Precision\t= 0.5044258230565134\n",
      "\t\t召回率 Recall   \t= 0.9285193289569658\n",
      "TP 1358 P 5484 FP 1108 N 3828\n",
      "测试特征feature36block_2\n",
      "\t\t精确率 Precision\t= 0.4610699924858284\n",
      "\t\t召回率 Recall   \t= 0.24762946754194018\n",
      "TP 331 P 5484 FP 269 N 3828\n",
      "测试特征feature36block_3\n",
      "\t\t精确率 Precision\t= 0.4620517937003877\n",
      "\t\t召回率 Recall   \t= 0.060357403355215174\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征feature37block_1\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征feature37block_2\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征feature37block_3\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5363 P 5484 FP 3718 N 3828\n",
      "测试特征feature38block_1\n",
      "\t\t精确率 Precision\t= 0.5017113289654928\n",
      "\t\t召回率 Recall   \t= 0.9779358132749818\n",
      "TP 534 P 5484 FP 446 N 3828\n",
      "测试特征feature38block_2\n",
      "\t\t精确率 Precision\t= 0.4552660836843343\n",
      "\t\t召回率 Recall   \t= 0.09737417943107221\n",
      "TP 118 P 5484 FP 150 N 3828\n",
      "测试特征feature38block_3\n",
      "\t\t精确率 Precision\t= 0.35447114660238055\n",
      "\t\t召回率 Recall   \t= 0.021517140773158278\n",
      "TP 4932 P 5484 FP 3364 N 3828\n",
      "测试特征feature39block_1\n",
      "\t\t精确率 Precision\t= 0.5057801312649165\n",
      "\t\t召回率 Recall   \t= 0.899343544857768\n",
      "TP 1725 P 5484 FP 1308 N 3828\n",
      "测试特征feature39block_2\n",
      "\t\t精确率 Precision\t= 0.47932068036490305\n",
      "\t\t召回率 Recall   \t= 0.31455142231947486\n",
      "TP 494 P 5484 FP 465 N 3828\n",
      "测试特征feature39block_3\n",
      "\t\t精确率 Precision\t= 0.4258033834921681\n",
      "\t\t召回率 Recall   \t= 0.09008023340627279\n",
      "TP 5092 P 5484 FP 3492 N 3828\n",
      "测试特征feature40block_1\n",
      "\t\t精确率 Precision\t= 0.5044258230565134\n",
      "\t\t召回率 Recall   \t= 0.9285193289569658\n",
      "TP 1358 P 5484 FP 1108 N 3828\n",
      "测试特征feature40block_2\n",
      "\t\t精确率 Precision\t= 0.4610699924858284\n",
      "\t\t召回率 Recall   \t= 0.24762946754194018\n",
      "TP 331 P 5484 FP 269 N 3828\n",
      "测试特征feature40block_3\n",
      "\t\t精确率 Precision\t= 0.4620517937003877\n",
      "\t\t召回率 Recall   \t= 0.060357403355215174\n",
      "TP 3213 P 5345 FP 2335 N 3762\n",
      "测试特征feature41block_1\n",
      "\t\t精确率 Precision\t= 0.49199627757884373\n",
      "\t\t召回率 Recall   \t= 0.6011225444340506\n",
      "TP 4501 P 5345 FP 3265 N 3762\n",
      "测试特征feature41block_2\n",
      "\t\t精确率 Precision\t= 0.4924578266166363\n",
      "\t\t召回率 Recall   \t= 0.8420954162768943\n",
      "TP 1019 P 5345 FP 600 N 3762\n",
      "测试特征feature41block_3\n",
      "\t\t精确率 Precision\t= 0.5444911552880358\n",
      "\t\t召回率 Recall   \t= 0.19064546304957905\n",
      "TP 3214 P 5345 FP 2307 N 3762\n",
      "测试特征feature42block_1\n",
      "\t\t精确率 Precision\t= 0.49508952651387894\n",
      "\t\t召回率 Recall   \t= 0.6013096351730589\n",
      "TP 4630 P 5345 FP 3326 N 3762\n",
      "测试特征feature42block_2\n",
      "\t\t精确率 Precision\t= 0.4948940959263861\n",
      "\t\t召回率 Recall   \t= 0.8662301216089804\n",
      "TP 2713 P 5345 FP 2018 N 3762\n",
      "测试特征feature42block_3\n",
      "\t\t精确率 Precision\t= 0.48618783951385347\n",
      "\t\t召回率 Recall   \t= 0.507577174929841\n",
      "TP 3257 P 5345 FP 2338 N 3762\n",
      "测试特征feature43block_1\n",
      "\t\t精确率 Precision\t= 0.4950751216875821\n",
      "\t\t召回率 Recall   \t= 0.609354536950421\n",
      "TP 4830 P 5345 FP 3439 N 3762\n",
      "测试特征feature43block_2\n",
      "\t\t精确率 Precision\t= 0.4971137627125692\n",
      "\t\t召回率 Recall   \t= 0.9036482694106641\n",
      "TP 574 P 5345 FP 363 N 3762\n",
      "测试特征feature43block_3\n",
      "\t\t精确率 Precision\t= 0.5267284333217958\n",
      "\t\t召回率 Recall   \t= 0.10739008419083255\n",
      "TP 3287 P 5345 FP 2368 N 3762\n",
      "测试特征feature44block_1\n",
      "\t\t精确率 Precision\t= 0.4941799538929803\n",
      "\t\t召回率 Recall   \t= 0.6149672591206735\n",
      "TP 4804 P 5345 FP 3382 N 3762\n",
      "测试特征feature44block_2\n",
      "\t\t精确率 Precision\t= 0.49994271003604535\n",
      "\t\t召回率 Recall   \t= 0.8987839101964453\n",
      "TP 4298 P 5345 FP 3097 N 3762\n",
      "测试特征feature44block_3\n",
      "\t\t精确率 Precision\t= 0.49412654108982557\n",
      "\t\t召回率 Recall   \t= 0.8041159962581852\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "result_list=pd.read_csv(\"/data/jupyter_root/dcube_data/no_name_add/result_list2_811.csv\")\n",
    "#print(result_list)\n",
    "def get_set(s):\n",
    "    s=re.sub('[ {}]','',s).split(',')\n",
    "    return set(map(int,s))\n",
    "for i in range(45):\n",
    "    try:\n",
    "        al=get_set(result_list.iloc[i,0])\n",
    "        get_no_name_PR(\"feature\"+str(i)+'block_1',al,get_set(result_list.iloc[i,1]))\n",
    "        get_no_name_PR(\"feature\"+str(i)+'block_2',al,get_set(result_list.iloc[i,2]))\n",
    "        get_no_name_PR(\"feature\"+str(i)+'block_3',al,get_set(result_list.iloc[i,3]))\n",
    "        #get_no_name_PR(\"feature\"+str(i)+'block_12',al,get_set(result_list.iloc[i,4]))\n",
    "        #get_no_name_PR(\"feature\"+str(i)+'block_123',al,get_set(result_list.iloc[i,5]))\n",
    "    except:\n",
    "        continue\n",
    "        print('false')\n",
    "#for i in range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TP 5538 P 5538 FP 3871 N 3871\n",
      "测试特征51_31\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5538 P 5538 FP 3871 N 3871\n",
      "测试特征51_32\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5538 P 5538 FP 3871 N 3871\n",
      "测试特征51_33\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 2032 P 5538 FP 1352 N 3871\n",
      "测试特征52_31\n",
      "\t\t精确率 Precision\t= 0.5123262517481643\n",
      "\t\t召回率 Recall   \t= 0.3669194655110148\n",
      "TP 3119 P 5538 FP 2238 N 3871\n",
      "测试特征52_32\n",
      "\t\t精确率 Precision\t= 0.49345269290406746\n",
      "\t\t召回率 Recall   \t= 0.563199711087035\n",
      "TP 318 P 5538 FP 274 N 3871\n",
      "测试特征52_33\n",
      "\t\t精确率 Precision\t= 0.4478905832141727\n",
      "\t\t召回率 Recall   \t= 0.05742145178764897\n",
      "TP 1038 P 5538 FP 720 N 3871\n",
      "测试特征53_31\n",
      "\t\t精确率 Precision\t= 0.5019198152060756\n",
      "\t\t召回率 Recall   \t= 0.18743228602383533\n",
      "TP 1748 P 5538 FP 1151 N 3871\n",
      "测试特征53_32\n",
      "\t\t精确率 Precision\t= 0.5149257127411184\n",
      "\t\t召回率 Recall   \t= 0.3156374142289635\n",
      "TP 44 P 5538 FP 18 N 3871\n",
      "测试特征53_33\n",
      "\t\t精确率 Precision\t= 0.6308109389351426\n",
      "\t\t召回率 Recall   \t= 0.007945106536655833\n",
      "TP 1153 P 5538 FP 821 N 3871\n",
      "测试特征54_31\n",
      "\t\t精确率 Precision\t= 0.4953698467729216\n",
      "\t\t召回率 Recall   \t= 0.20819790538100397\n",
      "TP 4238 P 5538 FP 2945 N 3871\n",
      "测试特征54_32\n",
      "\t\t精确率 Precision\t= 0.5014655182005598\n",
      "\t\t召回率 Recall   \t= 0.7652582159624414\n",
      "TP 1819 P 5538 FP 1378 N 3871\n",
      "测试特征54_33\n",
      "\t\t精确率 Precision\t= 0.47989414091313587\n",
      "\t\t召回率 Recall   \t= 0.32845792704947635\n",
      "TP 1157 P 5538 FP 826 N 3871\n",
      "测试特征55_31\n",
      "\t\t精确率 Precision\t= 0.49471779665276167\n",
      "\t\t召回率 Recall   \t= 0.20892018779342722\n",
      "TP 2641 P 5538 FP 1655 N 3871\n",
      "测试特征55_32\n",
      "\t\t精确率 Precision\t= 0.5272818947489055\n",
      "\t\t召回率 Recall   \t= 0.47688696280245574\n",
      "TP 63 P 5538 FP 53 N 3871\n",
      "测试特征55_33\n",
      "\t\t精确率 Precision\t= 0.45381261548939594\n",
      "\t\t召回率 Recall   \t= 0.011375947995666305\n",
      "TP 3398 P 5538 FP 1994 N 3871\n",
      "测试特征56_31\n",
      "\t\t精确率 Precision\t= 0.5436197819265074\n",
      "\t\t召回率 Recall   \t= 0.6135789093535572\n",
      "TP 1657 P 5538 FP 1306 N 3871\n",
      "测试特征56_32\n",
      "\t\t精确率 Precision\t= 0.4700158094801923\n",
      "\t\t召回率 Recall   \t= 0.2992054893463344\n",
      "TP 507 P 5538 FP 822 N 3871\n",
      "测试特征56_33\n",
      "\t\t精确率 Precision\t= 0.3012505462534496\n",
      "\t\t召回率 Recall   \t= 0.09154929577464789\n",
      "TP 3675 P 5538 FP 2123 N 3871\n",
      "测试特征57_31\n",
      "\t\t精确率 Precision\t= 0.5475068620567547\n",
      "\t\t召回率 Recall   \t= 0.6635969664138678\n",
      "TP 1940 P 5538 FP 1696 N 3871\n",
      "测试特征57_32\n",
      "\t\t精确率 Precision\t= 0.44430579046925756\n",
      "\t\t召回率 Recall   \t= 0.3503069700252799\n",
      "TP 9 P 5538 FP 127 N 3871\n",
      "测试特征57_33\n",
      "\t\t精确率 Precision\t= 0.04719676495092561\n",
      "\t\t召回率 Recall   \t= 0.0016251354279523294\n",
      "TP 5395 P 5538 FP 3602 N 3871\n",
      "测试特征58_31\n",
      "\t\t精确率 Precision\t= 0.5114636903808665\n",
      "\t\t召回率 Recall   \t= 0.9741784037558685\n",
      "TP 799 P 5538 FP 652 N 3871\n",
      "测试特征58_32\n",
      "\t\t精确率 Precision\t= 0.46137605995490555\n",
      "\t\t召回率 Recall   \t= 0.14427591188154568\n",
      "TP 9 P 5538 FP 123 N 3871\n",
      "测试特征58_33\n",
      "\t\t精确率 Precision\t= 0.048656937793028904\n",
      "\t\t召回率 Recall   \t= 0.0016251354279523294\n",
      "TP 5449 P 5538 FP 3637 N 3871\n",
      "测试特征59_31\n",
      "\t\t精确率 Precision\t= 0.5115360489935864\n",
      "\t\t召回率 Recall   \t= 0.9839292163235825\n",
      "TP 620 P 5538 FP 893 N 3871\n",
      "测试特征59_32\n",
      "\t\t精确率 Precision\t= 0.32673542030213515\n",
      "\t\t召回率 Recall   \t= 0.1119537739256049\n",
      "TP 34 P 5538 FP 97 N 3871\n",
      "测试特征59_33\n",
      "\t\t精确率 Precision\t= 0.19679126794258373\n",
      "\t\t召回率 Recall   \t= 0.0061394005055976884\n",
      "TP 3399 P 5538 FP 1994 N 3871\n",
      "测试特征60_31\n",
      "\t\t精确率 Precision\t= 0.5436927829947239\n",
      "\t\t召回率 Recall   \t= 0.613759479956663\n",
      "TP 2297 P 5538 FP 2348 N 3871\n",
      "测试特征60_32\n",
      "\t\t精确率 Precision\t= 0.4061074740153089\n",
      "\t\t召回率 Recall   \t= 0.4147706753340556\n",
      "TP 5 P 5538 FP 25 N 3871\n",
      "测试特征60_33\n",
      "\t\t精确率 Precision\t= 0.12265137353062323\n",
      "\t\t召回率 Recall   \t= 0.0009028530155290719\n",
      "TP 3674 P 5538 FP 2125 N 3871\n",
      "测试特征61_31\n",
      "\t\t精确率 Precision\t= 0.5472061427215319\n",
      "\t\t召回率 Recall   \t= 0.6634163958107621\n",
      "TP 1521 P 5538 FP 1722 N 3871\n",
      "测试特征61_32\n",
      "\t\t精确率 Precision\t= 0.3817235703286784\n",
      "\t\t召回率 Recall   \t= 0.2746478873239437\n",
      "TP 737 P 5538 FP 946 N 3871\n",
      "测试特征61_33\n",
      "\t\t精确率 Precision\t= 0.35256686491079015\n",
      "\t\t召回率 Recall   \t= 0.13308053448898519\n",
      "TP 5395 P 5538 FP 3606 N 3871\n",
      "测试特征62_31\n",
      "\t\t精确率 Precision\t= 0.5111863632299282\n",
      "\t\t召回率 Recall   \t= 0.9741784037558685\n",
      "TP 979 P 5538 FP 1377 N 3871\n",
      "测试特征62_32\n",
      "\t\t精确率 Precision\t= 0.33197822090686074\n",
      "\t\t召回率 Recall   \t= 0.17677862044059228\n",
      "TP 1 P 5538 FP 5 N 3871\n",
      "测试特征62_33\n",
      "\t\t精确率 Precision\t= 0.12265137353062325\n",
      "\t\t召回率 Recall   \t= 0.00018057060310581438\n",
      "TP 3062 P 5538 FP 1769 N 3871\n",
      "测试特征63_31\n",
      "\t\t精确率 Precision\t= 0.5474897509086027\n",
      "\t\t召回率 Recall   \t= 0.5529071867100036\n",
      "TP 1911 P 5538 FP 1449 N 3871\n",
      "测试特征63_32\n",
      "\t\t精确率 Precision\t= 0.4796693278575348\n",
      "\t\t召回率 Recall   \t= 0.34507042253521125\n",
      "TP 2034 P 5538 FP 2069 N 3871\n",
      "测试特征63_33\n",
      "\t\t精确率 Precision\t= 0.40728954709499443\n",
      "\t\t召回率 Recall   \t= 0.36728060671722645\n",
      "TP 3104 P 5484 FP 2045 N 3828\n",
      "测试特征64_31\n",
      "\t\t精确率 Precision\t= 0.514446359276391\n",
      "\t\t召回率 Recall   \t= 0.5660102115244348\n",
      "TP 1842 P 5484 FP 1353 N 3828\n",
      "测试特征64_32\n",
      "\t\t精确率 Precision\t= 0.48726158224557364\n",
      "\t\t召回率 Recall   \t= 0.3358862144420131\n",
      "TP 507 P 5484 FP 420 N 3828\n",
      "测试特征64_33\n",
      "\t\t精确率 Precision\t= 0.457295298199184\n",
      "\t\t召回率 Recall   \t= 0.09245076586433261\n",
      "TP 3168 P 5484 FP 2067 N 3828\n",
      "测试特征65_31\n",
      "\t\t精确率 Precision\t= 0.5168710691582648\n",
      "\t\t召回率 Recall   \t= 0.5776805251641138\n",
      "TP 1770 P 5484 FP 1303 N 3828\n",
      "测试特征65_32\n",
      "\t\t精确率 Precision\t= 0.48670762287076735\n",
      "\t\t召回率 Recall   \t= 0.3227571115973742\n",
      "TP 502 P 5484 FP 471 N 3828\n",
      "测试特征65_33\n",
      "\t\t精确率 Precision\t= 0.4265966940607643\n",
      "\t\t召回率 Recall   \t= 0.09153902261123267\n",
      "TP 5195 P 5484 FP 3613 N 3828\n",
      "测试特征66_31\n",
      "\t\t精确率 Precision\t= 0.5009164700427343\n",
      "\t\t召回率 Recall   \t= 0.9473012399708242\n",
      "TP 502 P 5484 FP 466 N 3828\n",
      "测试特征66_32\n",
      "\t\t精确率 Precision\t= 0.42920932725810773\n",
      "\t\t召回率 Recall   \t= 0.09153902261123267\n",
      "TP 284 P 5484 FP 221 N 3828\n",
      "测试特征66_33\n",
      "\t\t精确率 Precision\t= 0.47285652398574063\n",
      "\t\t召回率 Recall   \t= 0.051787016776075855\n",
      "TP 5247 P 5484 FP 3644 N 3828\n",
      "测试特征67_31\n",
      "\t\t精确率 Precision\t= 0.5012705515646277\n",
      "\t\t召回率 Recall   \t= 0.9567833698030634\n",
      "TP 204 P 5484 FP 201 N 3828\n",
      "测试特征67_32\n",
      "\t\t精确率 Precision\t= 0.4146737779816864\n",
      "\t\t召回率 Recall   \t= 0.037199124726477024\n",
      "TP 409 P 5484 FP 335 N 3828\n",
      "测试特征67_33\n",
      "\t\t精确率 Precision\t= 0.46010805244634406\n",
      "\t\t召回率 Recall   \t= 0.07458059810357404\n",
      "TP 2429 P 5484 FP 1473 N 3828\n",
      "测试特征68_31\n",
      "\t\t精确率 Precision\t= 0.5351136592790667\n",
      "\t\t召回率 Recall   \t= 0.4429248723559446\n",
      "TP 1990 P 5484 FP 1471 N 3828\n",
      "测试特征68_32\n",
      "\t\t精确率 Precision\t= 0.48567889541160025\n",
      "\t\t召回率 Recall   \t= 0.36287381473377095\n",
      "TP 1993 P 5484 FP 1663 N 3828\n",
      "测试特征68_33\n",
      "\t\t精确率 Precision\t= 0.45549944904489176\n",
      "\t\t召回率 Recall   \t= 0.36342086068563095\n",
      "TP 1 P 5484 FP 43 N 3828\n",
      "测试特征69_31\n",
      "\t\t精确率 Precision\t= 0.015973960941412117\n",
      "\t\t召回率 Recall   \t= 0.00018234865061998541\n",
      "TP 1415 P 5484 FP 784 N 3828\n",
      "测试特征69_32\n",
      "\t\t精确率 Precision\t= 0.5574904930755996\n",
      "\t\t召回率 Recall   \t= 0.2580233406272794\n",
      "TP 3506 P 5484 FP 2497 N 3828\n",
      "测试特征69_33\n",
      "\t\t精确率 Precision\t= 0.4949735411098616\n",
      "\t\t召回率 Recall   \t= 0.6393143690736689\n",
      "TP 1 P 5484 FP 38 N 3828\n",
      "测试特征70_31\n",
      "\t\t精确率 Precision\t= 0.01803788521345773\n",
      "\t\t召回率 Recall   \t= 0.00018234865061998541\n",
      "TP 2537 P 5484 FP 1524 N 3828\n",
      "测试特征70_32\n",
      "\t\t精确率 Precision\t= 0.5374675166409766\n",
      "\t\t召回率 Recall   \t= 0.462618526622903\n",
      "TP 2231 P 5484 FP 1692 N 3828\n",
      "测试特征70_33\n",
      "\t\t精确率 Precision\t= 0.4792734756382948\n",
      "\t\t召回率 Recall   \t= 0.40681983953318746\n",
      "TP 1216 P 5484 FP 697 N 3828\n",
      "测试特征71_31\n",
      "\t\t精确率 Precision\t= 0.5491023210976838\n",
      "\t\t召回率 Recall   \t= 0.22173595915390226\n",
      "TP 1705 P 5484 FP 1197 N 3828\n",
      "测试特征71_32\n",
      "\t\t精确率 Precision\t= 0.49856360296409286\n",
      "\t\t召回率 Recall   \t= 0.3109044493070751\n",
      "TP 2114 P 5484 FP 1568 N 3828\n",
      "测试特征71_33\n",
      "\t\t精确率 Precision\t= 0.4848268295874307\n",
      "\t\t召回率 Recall   \t= 0.38548504741064915\n",
      "TP 1772 P 5484 FP 982 N 3828\n",
      "测试特征72_32\n",
      "\t\t精确率 Precision\t= 0.5574404215998943\n",
      "\t\t召回率 Recall   \t= 0.32312180889861414\n",
      "TP 1808 P 5484 FP 1396 N 3828\n",
      "测试特征72_33\n",
      "\t\t精确率 Precision\t= 0.47480086011307926\n",
      "\t\t召回率 Recall   \t= 0.3296863603209336\n",
      "TP 1 P 5484 FP 39 N 3828\n",
      "测试特征73_31\n",
      "\t\t精确率 Precision\t= 0.017583507882262154\n",
      "\t\t召回率 Recall   \t= 0.00018234865061998541\n",
      "TP 920 P 5484 FP 460 N 3828\n",
      "测试特征73_32\n",
      "\t\t精确率 Precision\t= 0.582648401826484\n",
      "\t\t召回率 Recall   \t= 0.16776075857038658\n",
      "TP 3501 P 5484 FP 2086 N 3828\n",
      "测试特征73_33\n",
      "\t\t精确率 Precision\t= 0.5394945512846834\n",
      "\t\t召回率 Recall   \t= 0.638402625820569\n",
      "TP 1 P 5484 FP 26 N 3828\n",
      "测试特征74_31\n",
      "\t\t精确率 Precision\t= 0.026145397918203427\n",
      "\t\t召回率 Recall   \t= 0.00018234865061998541\n",
      "TP 1044 P 5484 FP 558 N 3828\n",
      "测试特征74_32\n",
      "\t\t精确率 Precision\t= 0.5663473017233462\n",
      "\t\t召回率 Recall   \t= 0.19037199124726478\n",
      "TP 1937 P 5484 FP 1408 N 3828\n",
      "测试特征74_33\n",
      "\t\t精确率 Precision\t= 0.48987084565139666\n",
      "\t\t召回率 Recall   \t= 0.3532093362509117\n",
      "TP 1 P 5484 FP 38 N 3828\n",
      "测试特征75_31\n",
      "\t\t精确率 Precision\t= 0.01803788521345773\n",
      "\t\t召回率 Recall   \t= 0.00018234865061998541\n",
      "TP 1093 P 5484 FP 567 N 3828\n",
      "测试特征75_32\n",
      "\t\t精确率 Precision\t= 0.5736673763462797\n",
      "\t\t召回率 Recall   \t= 0.19930707512764406\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TP 2066 P 5484 FP 1535 N 3828\n",
      "测试特征75_33\n",
      "\t\t精确率 Precision\t= 0.48440298732349957\n",
      "\t\t召回率 Recall   \t= 0.3767323121808899\n",
      "TP 3 P 5484 FP 36 N 3828\n",
      "测试特征76_31\n",
      "\t\t精确率 Precision\t= 0.05497156643115629\n",
      "\t\t召回率 Recall   \t= 0.0005470459518599562\n",
      "TP 1797 P 5484 FP 1273 N 3828\n",
      "测试特征76_32\n",
      "\t\t精确率 Precision\t= 0.4963125668828852\n",
      "\t\t召回率 Recall   \t= 0.3276805251641138\n",
      "TP 3043 P 5484 FP 2077 N 3828\n",
      "测试特征76_33\n",
      "\t\t精确率 Precision\t= 0.5056065244860946\n",
      "\t\t召回率 Recall   \t= 0.5548869438366156\n",
      "TP 1 P 5484 FP 38 N 3828\n",
      "测试特征77_31\n",
      "\t\t精确率 Precision\t= 0.01803788521345773\n",
      "\t\t召回率 Recall   \t= 0.00018234865061998541\n",
      "TP 236 P 5484 FP 225 N 3828\n",
      "测试特征77_32\n",
      "\t\t精确率 Precision\t= 0.42268498503725244\n",
      "\t\t召回率 Recall   \t= 0.043034281546316555\n",
      "TP 1757 P 5484 FP 1203 N 3828\n",
      "测试特征77_33\n",
      "\t\t精确率 Precision\t= 0.5048241213271917\n",
      "\t\t召回率 Recall   \t= 0.32038657913931434\n",
      "TP 57 P 5484 FP 91 N 3828\n",
      "测试特征78_31\n",
      "\t\t精确率 Precision\t= 0.30421616195415757\n",
      "\t\t召回率 Recall   \t= 0.010393873085339168\n",
      "TP 1398 P 5484 FP 995 N 3828\n",
      "测试特征78_32\n",
      "\t\t精确率 Precision\t= 0.4951408773622508\n",
      "\t\t召回率 Recall   \t= 0.2549234135667396\n",
      "TP 3 P 5484 FP 13 N 3828\n",
      "测试特征79_31\n",
      "\t\t精确率 Precision\t= 0.13873586546825165\n",
      "\t\t召回率 Recall   \t= 0.0005470459518599562\n",
      "TP 276 P 5484 FP 278 N 3828\n",
      "测试特征79_32\n",
      "\t\t精确率 Precision\t= 0.4093356269468595\n",
      "\t\t召回率 Recall   \t= 0.05032822757111598\n",
      "TP 2690 P 5484 FP 1699 N 3828\n",
      "测试特征79_33\n",
      "\t\t精确率 Precision\t= 0.5249814475272445\n",
      "\t\t召回率 Recall   \t= 0.49051787016776077\n",
      "TP 3302 P 5345 FP 2395 N 3762\n",
      "测试特征80_31\n",
      "\t\t精确率 Precision\t= 0.49248414141171065\n",
      "\t\t召回率 Recall   \t= 0.6177736202057998\n",
      "TP 680 P 5345 FP 488 N 3762\n",
      "测试特征80_32\n",
      "\t\t精确率 Precision\t= 0.49514179757360854\n",
      "\t\t召回率 Recall   \t= 0.12722170252572498\n",
      "TP 1513 P 5345 FP 1049 N 3762\n",
      "测试特征80_33\n",
      "\t\t精确率 Precision\t= 0.5037615019845892\n",
      "\t\t召回率 Recall   \t= 0.28306828811973805\n",
      "TP 1857 P 5345 FP 1272 N 3762\n",
      "测试特征81_31\n",
      "\t\t精确率 Precision\t= 0.5067898335523415\n",
      "\t\t召回率 Recall   \t= 0.34742750233863423\n",
      "TP 3356 P 5345 FP 2533 N 3762\n",
      "测试特征81_32\n",
      "\t\t精确率 Precision\t= 0.48254075222068116\n",
      "\t\t召回率 Recall   \t= 0.6278765201122545\n",
      "TP 133 P 5345 FP 77 N 3762\n",
      "测试特征81_33\n",
      "\t\t精确率 Precision\t= 0.548678544287765\n",
      "\t\t召回率 Recall   \t= 0.024883068288119738\n",
      "TP 1912 P 5345 FP 1321 N 3762\n",
      "测试特征82_31\n",
      "\t\t精确率 Precision\t= 0.504637360896537\n",
      "\t\t召回率 Recall   \t= 0.3577174929840973\n",
      "TP 3502 P 5345 FP 2620 N 3762\n",
      "测试特征82_32\n",
      "\t\t精确率 Precision\t= 0.48474201447442283\n",
      "\t\t召回率 Recall   \t= 0.6551917680074836\n",
      "TP 257 P 5345 FP 168 N 3762\n",
      "测试特征82_33\n",
      "\t\t精确率 Precision\t= 0.5184669191342315\n",
      "\t\t召回率 Recall   \t= 0.0480823199251637\n",
      "TP 1912 P 5345 FP 1319 N 3762\n",
      "测试特征83_31\n",
      "\t\t精确率 Precision\t= 0.5050161135305844\n",
      "\t\t召回率 Recall   \t= 0.3577174929840973\n",
      "TP 2469 P 5345 FP 1999 N 3762\n",
      "测试特征83_32\n",
      "\t\t精确率 Precision\t= 0.4650459446995356\n",
      "\t\t召回率 Recall   \t= 0.4619270346117867\n",
      "TP 552 P 5345 FP 340 N 3762\n",
      "测试特征83_33\n",
      "\t\t精确率 Precision\t= 0.5332985440907424\n",
      "\t\t召回率 Recall   \t= 0.10327408793264733\n",
      "TP 2 P 4800 FP 2 N 2608\n",
      "测试特征84_31\n",
      "\t\t精确率 Precision\t= 0.35205183585313177\n",
      "\t\t召回率 Recall   \t= 0.0004166666666666667\n",
      "TP 392 P 4800 FP 266 N 2608\n",
      "测试特征84_32\n",
      "\t\t精确率 Precision\t= 0.4446609508963367\n",
      "\t\t召回率 Recall   \t= 0.08166666666666667\n",
      "TP 2 P 4800 FP 3 N 2608\n",
      "测试特征85_32\n",
      "\t\t精确率 Precision\t= 0.265905383360522\n",
      "\t\t召回率 Recall   \t= 0.0004166666666666667\n",
      "TP 1 P 4800 FP 0 N 2608\n",
      "测试特征85_33\n",
      "\t\t精确率 Precision\t= 1.0\n",
      "\t\t召回率 Recall   \t= 0.00020833333333333335\n",
      "TP 3 P 4800 FP 2 N 2608\n",
      "测试特征86_32\n",
      "\t\t精确率 Precision\t= 0.4490358126721763\n",
      "\t\t召回率 Recall   \t= 0.000625\n",
      "TP 396 P 4800 FP 273 N 2608\n",
      "测试特征86_33\n",
      "\t\t精确率 Precision\t= 0.44075712881022616\n",
      "\t\t召回率 Recall   \t= 0.0825\n",
      "TP 2 P 4800 FP 2 N 2608\n",
      "测试特征87_31\n",
      "\t\t精确率 Precision\t= 0.35205183585313177\n",
      "\t\t召回率 Recall   \t= 0.0004166666666666667\n",
      "TP 415 P 4800 FP 285 N 2608\n",
      "测试特征87_32\n",
      "\t\t精确率 Precision\t= 0.4417055731496295\n",
      "\t\t召回率 Recall   \t= 0.08645833333333333\n",
      "TP 2556 P 4800 FP 1316 N 2608\n",
      "测试特征88_31\n",
      "\t\t精确率 Precision\t= 0.5134503615847618\n",
      "\t\t召回率 Recall   \t= 0.5325\n",
      "TP 3596 P 4800 FP 2023 N 2608\n",
      "测试特征88_32\n",
      "\t\t精确率 Precision\t= 0.4913029484144812\n",
      "\t\t召回率 Recall   \t= 0.7491666666666666\n",
      "TP 656 P 4800 FP 388 N 2608\n",
      "测试特征88_33\n",
      "\t\t精确率 Precision\t= 0.47879352342742515\n",
      "\t\t召回率 Recall   \t= 0.13666666666666666\n",
      "TP 2416 P 4800 FP 1230 N 2608\n",
      "测试特征89_31\n",
      "\t\t精确率 Precision\t= 0.5162609726169626\n",
      "\t\t召回率 Recall   \t= 0.5033333333333333\n",
      "TP 3590 P 4800 FP 2022 N 2608\n",
      "测试特征89_32\n",
      "\t\t精确率 Precision\t= 0.4910091712327043\n",
      "\t\t召回率 Recall   \t= 0.7479166666666667\n",
      "TP 466 P 4800 FP 261 N 2608\n",
      "测试特征89_33\n",
      "\t\t精确率 Precision\t= 0.49240882158461796\n",
      "\t\t召回率 Recall   \t= 0.09708333333333333\n",
      "TP 2395 P 4800 FP 1240 N 2608\n",
      "测试特征90_31\n",
      "\t\t精确率 Precision\t= 0.5120575562215941\n",
      "\t\t召回率 Recall   \t= 0.49895833333333334\n",
      "TP 3059 P 4800 FP 1693 N 2608\n",
      "测试特征90_32\n",
      "\t\t精确率 Precision\t= 0.4953885528013933\n",
      "\t\t召回率 Recall   \t= 0.6372916666666667\n",
      "TP 1517 P 4800 FP 910 N 2608\n",
      "测试特征90_33\n",
      "\t\t精确率 Precision\t= 0.47527346325280484\n",
      "\t\t召回率 Recall   \t= 0.31604166666666667\n",
      "TP 1569 P 4800 FP 857 N 2608\n",
      "测试特征91_31\n",
      "\t\t精确率 Precision\t= 0.4986808931318697\n",
      "\t\t召回率 Recall   \t= 0.326875\n",
      "TP 4042 P 4800 FP 2232 N 2608\n",
      "测试特征91_32\n",
      "\t\t精确率 Precision\t= 0.49595241357194797\n",
      "\t\t召回率 Recall   \t= 0.8420833333333333\n",
      "TP 499 P 4800 FP 276 N 2608\n",
      "测试特征91_33\n",
      "\t\t精确率 Precision\t= 0.4955433570736641\n",
      "\t\t召回率 Recall   \t= 0.10395833333333333\n",
      "TP 1855 P 4800 FP 939 N 2608\n",
      "测试特征92_31\n",
      "\t\t精确率 Precision\t= 0.5176906679907202\n",
      "\t\t召回率 Recall   \t= 0.38645833333333335\n",
      "TP 3996 P 4800 FP 2209 N 2608\n",
      "测试特征92_32\n",
      "\t\t精确率 Precision\t= 0.4956805230859147\n",
      "\t\t召回率 Recall   \t= 0.8325\n",
      "TP 656 P 4800 FP 449 N 2608\n",
      "测试特征92_33\n",
      "\t\t精确率 Precision\t= 0.44253149469432346\n",
      "\t\t召回率 Recall   \t= 0.13666666666666666\n",
      "TP 1356 P 4800 FP 727 N 2608\n",
      "测试特征93_31\n",
      "\t\t精确率 Precision\t= 0.5033338798710171\n",
      "\t\t召回率 Recall   \t= 0.2825\n",
      "TP 4185 P 4800 FP 2263 N 2608\n",
      "测试特征93_32\n",
      "\t\t精确率 Precision\t= 0.5011957635804578\n",
      "\t\t召回率 Recall   \t= 0.871875\n",
      "TP 562 P 4800 FP 379 N 2608\n",
      "测试特征93_33\n",
      "\t\t精确率 Precision\t= 0.4461925126396695\n",
      "\t\t召回率 Recall   \t= 0.11708333333333333\n",
      "TP 2866 P 4800 FP 1428 N 2608\n",
      "测试特征94_31\n",
      "\t\t精确率 Precision\t= 0.5216390228215259\n",
      "\t\t召回率 Recall   \t= 0.5970833333333333\n",
      "TP 2207 P 4800 FP 1241 N 2608\n",
      "测试特征94_32\n",
      "\t\t精确率 Precision\t= 0.4914219285531821\n",
      "\t\t召回率 Recall   \t= 0.45979166666666665\n",
      "TP 667 P 4800 FP 503 N 2608\n",
      "测试特征94_33\n",
      "\t\t精确率 Precision\t= 0.41876812738568914\n",
      "\t\t召回率 Recall   \t= 0.13895833333333332\n",
      "TP 1523 P 4800 FP 750 N 2608\n",
      "测试特征95_31\n",
      "\t\t精确率 Precision\t= 0.5245631792143248\n",
      "\t\t召回率 Recall   \t= 0.3172916666666667\n",
      "TP 4211 P 4800 FP 2301 N 2608\n",
      "测试特征95_32\n",
      "\t\t精确率 Precision\t= 0.4985810198787965\n",
      "\t\t召回率 Recall   \t= 0.8772916666666667\n",
      "TP 779 P 4800 FP 492 N 2608\n",
      "测试特征95_33\n",
      "\t\t精确率 Precision\t= 0.46244587128565035\n",
      "\t\t召回率 Recall   \t= 0.16229166666666667\n",
      "TP 4915 P 5538 FP 2721 N 3871\n",
      "测试特征96_31\n",
      "\t\t精确率 Precision\t= 0.5580302522406381\n",
      "\t\t召回率 Recall   \t= 0.8875045142650776\n",
      "TP 586 P 5538 FP 1194 N 3871\n",
      "测试特征96_32\n",
      "\t\t精确率 Precision\t= 0.2554287473462348\n",
      "\t\t召回率 Recall   \t= 0.10581437342000723\n",
      "TP 159 P 5538 FP 527 N 3871\n",
      "测试特征96_33\n",
      "\t\t精确率 Precision\t= 0.17416139999405775\n",
      "\t\t召回率 Recall   \t= 0.028710725893824486\n",
      "TP 4898 P 5538 FP 2727 N 3871\n",
      "测试特征97_31\n",
      "\t\t精确率 Precision\t= 0.5566320215050758\n",
      "\t\t召回率 Recall   \t= 0.8844348140122787\n",
      "TP 998 P 5538 FP 1731 N 3871\n",
      "测试特征97_32\n",
      "\t\t精确率 Precision\t= 0.28724098734707276\n",
      "\t\t召回率 Recall   \t= 0.18020946189960274\n",
      "TP 148 P 5538 FP 500 N 3871\n",
      "测试特征97_33\n",
      "\t\t精确率 Precision\t= 0.17143140984132416\n",
      "\t\t召回率 Recall   \t= 0.026724449259660527\n",
      "TP 5447 P 5538 FP 3639 N 3871\n",
      "测试特征98_31\n",
      "\t\t精确率 Precision\t= 0.5113069536464551\n",
      "\t\t召回率 Recall   \t= 0.9835680751173709\n",
      "TP 299 P 5538 FP 204 N 3871\n",
      "测试特征98_32\n",
      "\t\t精确率 Precision\t= 0.5060504612446501\n",
      "\t\t召回率 Recall   \t= 0.0539906103286385\n",
      "TP 220 P 5538 FP 744 N 3871\n",
      "测试特征98_33\n",
      "\t\t精确率 Precision\t= 0.17128690647343103\n",
      "\t\t召回率 Recall   \t= 0.03972553268327916\n",
      "TP 5466 P 5538 FP 3655 N 3871\n",
      "测试特征99_31\n",
      "\t\t精确率 Precision\t= 0.5110807956932462\n",
      "\t\t召回率 Recall   \t= 0.9869989165763814\n",
      "TP 266 P 5538 FP 386 N 3871\n",
      "测试特征99_32\n",
      "\t\t精确率 Precision\t= 0.32509343761385684\n",
      "\t\t召回率 Recall   \t= 0.04803178042614662\n",
      "TP 239 P 5538 FP 716 N 3871\n",
      "测试特征99_33\n",
      "\t\t精确率 Precision\t= 0.18918152935857502\n",
      "\t\t召回率 Recall   \t= 0.043156374142289636\n",
      "TP 4916 P 5538 FP 2724 N 3871\n",
      "测试特征100_31\n",
      "\t\t精确率 Precision\t= 0.5578086437810923\n",
      "\t\t召回率 Recall   \t= 0.8876850848681834\n",
      "TP 760 P 5538 FP 1602 N 3871\n",
      "测试特征100_32\n",
      "\t\t精确率 Precision\t= 0.24902664976896582\n",
      "\t\t召回率 Recall   \t= 0.13723365836041893\n",
      "TP 56 P 5538 FP 203 N 3871\n",
      "测试特征100_33\n",
      "\t\t精确率 Precision\t= 0.1616537036070366\n",
      "\t\t召回率 Recall   \t= 0.010111953773925604\n",
      "TP 4898 P 5538 FP 2731 N 3871\n",
      "测试特征101_31\n",
      "\t\t精确率 Precision\t= 0.5562702577798265\n",
      "\t\t召回率 Recall   \t= 0.8844348140122787\n",
      "TP 963 P 5538 FP 1723 N 3871\n",
      "测试特征101_32\n",
      "\t\t精确率 Precision\t= 0.28092268827732736\n",
      "\t\t召回率 Recall   \t= 0.17388949079089924\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TP 257 P 5538 FP 307 N 3871\n",
      "测试特征101_33\n",
      "\t\t精确率 Precision\t= 0.36914367388951375\n",
      "\t\t召回率 Recall   \t= 0.046406644998194295\n",
      "TP 5447 P 5538 FP 3643 N 3871\n",
      "测试特征102_31\n",
      "\t\t精确率 Precision\t= 0.511032440867875\n",
      "\t\t召回率 Recall   \t= 0.9835680751173709\n",
      "TP 719 P 5538 FP 1282 N 3871\n",
      "测试特征102_32\n",
      "\t\t精确率 Precision\t= 0.281620849613451\n",
      "\t\t召回率 Recall   \t= 0.12983026363308053\n",
      "TP 5 P 5538 FP 26 N 3871\n",
      "测试特征102_33\n",
      "\t\t精确率 Precision\t= 0.1184929871497401\n",
      "\t\t召回率 Recall   \t= 0.0009028530155290719\n",
      "TP 5466 P 5538 FP 3660 N 3871\n",
      "测试特征103_31\n",
      "\t\t精确率 Precision\t= 0.5107391948714064\n",
      "\t\t召回率 Recall   \t= 0.9869989165763814\n",
      "TP 103 P 5538 FP 490 N 3871\n",
      "测试特征103_32\n",
      "\t\t精确率 Precision\t= 0.12810743580458775\n",
      "\t\t召回率 Recall   \t= 0.018598772119898882\n",
      "TP 412 P 5538 FP 314 N 3871\n",
      "测试特征103_33\n",
      "\t\t精确率 Precision\t= 0.4783909215474068\n",
      "\t\t召回率 Recall   \t= 0.07439508847959553\n",
      "TP 5334 P 5484 FP 3734 N 3828\n",
      "测试特征104_31\n",
      "\t\t精确率 Precision\t= 0.4992822736256978\n",
      "\t\t召回率 Recall   \t= 0.9726477024070022\n",
      "TP 195 P 5484 FP 133 N 3828\n",
      "测试特征104_32\n",
      "\t\t精确率 Precision\t= 0.5057892768282569\n",
      "\t\t召回率 Recall   \t= 0.03555798687089715\n",
      "TP 113 P 5484 FP 59 N 3828\n",
      "测试特征104_33\n",
      "\t\t精确率 Precision\t= 0.5720837962228218\n",
      "\t\t召回率 Recall   \t= 0.02060539752005835\n",
      "TP 5303 P 5484 FP 3692 N 3828\n",
      "测试特征105_31\n",
      "\t\t精确率 Precision\t= 0.5006530229799571\n",
      "\t\t召回率 Recall   \t= 0.9669948942377826\n",
      "TP 277 P 5484 FP 217 N 3828\n",
      "测试特征105_32\n",
      "\t\t精确率 Precision\t= 0.47118891709148303\n",
      "\t\t召回率 Recall   \t= 0.05051057622173596\n",
      "TP 233 P 5484 FP 205 N 3828\n",
      "测试特征105_33\n",
      "\t\t精确率 Precision\t= 0.44239101968906985\n",
      "\t\t召回率 Recall   \t= 0.0424872355944566\n",
      "TP 5255 P 5484 FP 3657 N 3828\n",
      "测试特征106_31\n",
      "\t\t精确率 Precision\t= 0.500761143675129\n",
      "\t\t召回率 Recall   \t= 0.9582421590080233\n",
      "TP 480 P 5484 FP 447 N 3828\n",
      "测试特征106_32\n",
      "\t\t精确率 Precision\t= 0.42842873091418837\n",
      "\t\t召回率 Recall   \t= 0.087527352297593\n",
      "TP 155 P 5484 FP 111 N 3828\n",
      "测试特征106_33\n",
      "\t\t精确率 Precision\t= 0.49360100626921694\n",
      "\t\t召回率 Recall   \t= 0.028264040846097738\n",
      "TP 5279 P 5484 FP 3678 N 3828\n",
      "测试特征107_31\n",
      "\t\t精确率 Precision\t= 0.5004688177501088\n",
      "\t\t召回率 Recall   \t= 0.962618526622903\n",
      "TP 546 P 5484 FP 398 N 3828\n",
      "测试特征107_32\n",
      "\t\t精确率 Precision\t= 0.48917036454530133\n",
      "\t\t召回率 Recall   \t= 0.09956236323851203\n",
      "TP 85 P 5484 FP 61 N 3828\n",
      "测试特征107_33\n",
      "\t\t精确率 Precision\t= 0.49307171952283974\n",
      "\t\t召回率 Recall   \t= 0.01549963530269876\n",
      "TP 4369 P 5484 FP 2870 N 3828\n",
      "测试特征108_31\n",
      "\t\t精确率 Precision\t= 0.5151777935246392\n",
      "\t\t召回率 Recall   \t= 0.7966812545587163\n",
      "TP 1867 P 5484 FP 1584 N 3828\n",
      "测试特征108_32\n",
      "\t\t精确率 Precision\t= 0.4513759785245642\n",
      "\t\t召回率 Recall   \t= 0.34044493070751275\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征108_33\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 4264 P 5484 FP 2767 N 3828\n",
      "测试特征109_31\n",
      "\t\t精确率 Precision\t= 0.5182298403457872\n",
      "\t\t召回率 Recall   \t= 0.7775346462436178\n",
      "TP 2058 P 5484 FP 1764 N 3828\n",
      "测试特征109_32\n",
      "\t\t精确率 Precision\t= 0.44884422110552763\n",
      "\t\t召回率 Recall   \t= 0.37527352297593\n",
      "TP 54 P 5484 FP 60 N 3828\n",
      "测试特征109_33\n",
      "\t\t精确率 Precision\t= 0.3858352371993012\n",
      "\t\t召回率 Recall   \t= 0.009846827133479213\n",
      "TP 3873 P 5484 FP 2471 N 3828\n",
      "测试特征110_31\n",
      "\t\t精确率 Precision\t= 0.5224634144897481\n",
      "\t\t召回率 Recall   \t= 0.7062363238512035\n",
      "TP 3094 P 5484 FP 2426 N 3828\n",
      "测试特征110_32\n",
      "\t\t精确率 Precision\t= 0.47096486657237696\n",
      "\t\t召回率 Recall   \t= 0.5641867250182349\n",
      "TP 17 P 5484 FP 18 N 3828\n",
      "测试特征110_33\n",
      "\t\t精确率 Precision\t= 0.3973184848706865\n",
      "\t\t召回率 Recall   \t= 0.003099927060539752\n",
      "TP 2427 P 5484 FP 1450 N 3828\n",
      "测试特征111_31\n",
      "\t\t精确率 Precision\t= 0.538821724826932\n",
      "\t\t召回率 Recall   \t= 0.4425601750547046\n",
      "TP 3598 P 5484 FP 2791 N 3828\n",
      "测试特征111_32\n",
      "\t\t精确率 Precision\t= 0.47364591917710486\n",
      "\t\t召回率 Recall   \t= 0.6560904449307076\n",
      "TP 177 P 5484 FP 157 N 3828\n",
      "测试特征111_33\n",
      "\t\t精确率 Precision\t= 0.44038779521417654\n",
      "\t\t召回率 Recall   \t= 0.032275711159737416\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征112_31\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征112_32\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征112_33\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 1881 P 5484 FP 1302 N 3828\n",
      "测试特征113_31\n",
      "\t\t精确率 Precision\t= 0.5021024172149687\n",
      "\t\t召回率 Recall   \t= 0.34299781181619254\n",
      "TP 3619 P 5484 FP 2577 N 3828\n",
      "测试特征113_32\n",
      "\t\t精确率 Precision\t= 0.49502004588041076\n",
      "\t\t召回率 Recall   \t= 0.6599197665937272\n",
      "TP 239 P 5484 FP 206 N 3828\n",
      "测试特征113_33\n",
      "\t\t精确率 Precision\t= 0.44746835071574037\n",
      "\t\t召回率 Recall   \t= 0.04358132749817651\n",
      "TP 5393 P 5484 FP 3748 N 3828\n",
      "测试特征114_31\n",
      "\t\t精确率 Precision\t= 0.5010967892082117\n",
      "\t\t召回率 Recall   \t= 0.9834062727935813\n",
      "TP 430 P 5484 FP 418 N 3828\n",
      "测试特征114_32\n",
      "\t\t精确率 Precision\t= 0.41795146802520444\n",
      "\t\t召回率 Recall   \t= 0.07840991976659373\n",
      "TP 38 P 5484 FP 34 N 3828\n",
      "测试特征114_33\n",
      "\t\t精确率 Precision\t= 0.4382501807664497\n",
      "\t\t召回率 Recall   \t= 0.006929248723559446\n",
      "TP 5418 P 5484 FP 3769 N 3828\n",
      "测试特征115_31\n",
      "\t\t精确率 Precision\t= 0.5008561844802979\n",
      "\t\t召回率 Recall   \t= 0.9879649890590809\n",
      "TP 331 P 5484 FP 269 N 3828\n",
      "测试特征115_32\n",
      "\t\t精确率 Precision\t= 0.4620517937003877\n",
      "\t\t召回率 Recall   \t= 0.060357403355215174\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征115_33\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征116_31\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征116_32\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征116_33\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 1888 P 5484 FP 1305 N 3828\n",
      "测试特征117_31\n",
      "\t\t精确率 Precision\t= 0.5024556649650401\n",
      "\t\t召回率 Recall   \t= 0.34427425237053244\n",
      "TP 2883 P 5484 FP 1947 N 3828\n",
      "测试特征117_32\n",
      "\t\t精确率 Precision\t= 0.5082615990662386\n",
      "\t\t召回率 Recall   \t= 0.5257111597374179\n",
      "TP 1066 P 5484 FP 822 N 3828\n",
      "测试特征117_33\n",
      "\t\t精确率 Precision\t= 0.4751295220956033\n",
      "\t\t召回率 Recall   \t= 0.19438366156090445\n",
      "TP 5393 P 5484 FP 3748 N 3828\n",
      "测试特征118_31\n",
      "\t\t精确率 Precision\t= 0.5010967892082117\n",
      "\t\t召回率 Recall   \t= 0.9834062727935813\n",
      "TP 430 P 5484 FP 418 N 3828\n",
      "测试特征118_32\n",
      "\t\t精确率 Precision\t= 0.41795146802520444\n",
      "\t\t召回率 Recall   \t= 0.07840991976659373\n",
      "TP 38 P 5484 FP 34 N 3828\n",
      "测试特征118_33\n",
      "\t\t精确率 Precision\t= 0.4382501807664497\n",
      "\t\t召回率 Recall   \t= 0.006929248723559446\n",
      "TP 5418 P 5484 FP 3769 N 3828\n",
      "测试特征119_31\n",
      "\t\t精确率 Precision\t= 0.5008561844802979\n",
      "\t\t召回率 Recall   \t= 0.9879649890590809\n",
      "TP 331 P 5484 FP 269 N 3828\n",
      "测试特征119_32\n",
      "\t\t精确率 Precision\t= 0.4620517937003877\n",
      "\t\t召回率 Recall   \t= 0.060357403355215174\n",
      "TP 5484 P 5484 FP 3828 N 3828\n",
      "测试特征119_33\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 3302 P 5345 FP 2395 N 3762\n",
      "测试特征120_31\n",
      "\t\t精确率 Precision\t= 0.49248414141171065\n",
      "\t\t召回率 Recall   \t= 0.6177736202057998\n",
      "TP 1989 P 5345 FP 1386 N 3762\n",
      "测试特征120_32\n",
      "\t\t精确率 Precision\t= 0.5024998005478286\n",
      "\t\t召回率 Recall   \t= 0.3721234798877456\n",
      "TP 449 P 5345 FP 308 N 3762\n",
      "测试特征120_33\n",
      "\t\t精确率 Precision\t= 0.5064277186710552\n",
      "\t\t召回率 Recall   \t= 0.08400374181478017\n",
      "TP 3279 P 5345 FP 2370 N 3762\n",
      "测试特征121_31\n",
      "\t\t精确率 Precision\t= 0.49335982269183587\n",
      "\t\t召回率 Recall   \t= 0.6134705332086062\n",
      "TP 1959 P 5345 FP 1376 N 3762\n",
      "测试特征121_32\n",
      "\t\t精确率 Precision\t= 0.500510646285729\n",
      "\t\t召回率 Recall   \t= 0.366510757717493\n",
      "TP 542 P 5345 FP 410 N 3762\n",
      "测试特征121_33\n",
      "\t\t精确率 Precision\t= 0.4819823120639062\n",
      "\t\t召回率 Recall   \t= 0.10140318054256314\n",
      "TP 3399 P 5345 FP 2457 N 3762\n",
      "测试特征122_31\n",
      "\t\t精确率 Precision\t= 0.4933327361042678\n",
      "\t\t召回率 Recall   \t= 0.6359214218896164\n",
      "TP 1898 P 5345 FP 1325 N 3762\n",
      "测试特征122_32\n",
      "\t\t精确率 Precision\t= 0.5020443453956895\n",
      "\t\t召回率 Recall   \t= 0.3550982226379794\n",
      "TP 463 P 5345 FP 327 N 3762\n",
      "测试特征122_33\n",
      "\t\t精确率 Precision\t= 0.49913901824868656\n",
      "\t\t召回率 Recall   \t= 0.08662301216089803\n",
      "TP 3403 P 5345 FP 2461 N 3762\n",
      "测试特征123_31\n",
      "\t\t精确率 Precision\t= 0.4932201182063691\n",
      "\t\t召回率 Recall   \t= 0.6366697848456502\n",
      "TP 1897 P 5345 FP 1320 N 3762\n",
      "测试特征123_32\n",
      "\t\t精确率 Precision\t= 0.5028577540703811\n",
      "\t\t召回率 Recall   \t= 0.354911131898971\n",
      "TP 452 P 5345 FP 312 N 3762\n",
      "测试特征123_33\n",
      "\t\t精确率 Precision\t= 0.5048668908904345\n",
      "\t\t召回率 Recall   \t= 0.08456501403180543\n",
      "TP 1412 P 4800 FP 775 N 2608\n",
      "测试特征124_31\n",
      "\t\t精确率 Precision\t= 0.4974668003873289\n",
      "\t\t召回率 Recall   \t= 0.2941666666666667\n",
      "TP 3388 P 4800 FP 1833 N 2608\n",
      "测试特征124_32\n",
      "\t\t精确率 Precision\t= 0.5010633819174264\n",
      "\t\t召回率 Recall   \t= 0.7058333333333333\n",
      "TP 4800 P 4800 FP 2608 N 2608\n",
      "测试特征124_33\n",
      "\t\t精确率 Precision\t= 0.5\n",
      "\t\t召回率 Recall   \t= 1.0\n",
      "TP 1375 P 4800 FP 764 N 2608\n",
      "测试特征125_31\n",
      "\t\t精确率 Precision\t= 0.4944024706336514\n",
      "\t\t召回率 Recall   \t= 0.2864583333333333\n",
      "TP 3550 P 4800 FP 1954 N 2608\n",
      "测试特征125_32\n",
      "\t\t精确率 Precision\t= 0.4967592393870456\n",
      "\t\t召回率 Recall   \t= 0.7395833333333334\n",
      "TP 120 P 4800 FP 111 N 2608\n",
      "测试特征125_33\n",
      "\t\t精确率 Precision\t= 0.3700340522133939\n",
      "\t\t召回率 Recall   \t= 0.025\n",
      "TP 1403 P 4800 FP 772 N 2608\n",
      "测试特征126_31\n",
      "\t\t精确率 Precision\t= 0.49683785621642057\n",
      "\t\t召回率 Recall   \t= 0.29229166666666667\n",
      "TP 2946 P 4800 FP 1501 N 2608\n",
      "测试特征126_32\n",
      "\t\t精确率 Precision\t= 0.5160655906836985\n",
      "\t\t召回率 Recall   \t= 0.61375\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TP 1200 P 4800 FP 776 N 2608\n",
      "测试特征126_33\n",
      "\t\t精确率 Precision\t= 0.4565826330532212\n",
      "\t\t召回率 Recall   \t= 0.25\n",
      "TP 1410 P 4800 FP 774 N 2608\n",
      "测试特征127_31\n",
      "\t\t精确率 Precision\t= 0.4974352314784754\n",
      "\t\t召回率 Recall   \t= 0.29375\n",
      "TP 3555 P 4800 FP 1951 N 2608\n",
      "测试特征127_32\n",
      "\t\t精确率 Precision\t= 0.49749520289500454\n",
      "\t\t召回率 Recall   \t= 0.740625\n",
      "TP 16 P 4800 FP 10 N 2608\n",
      "测试特征127_33\n",
      "\t\t精确率 Precision\t= 0.46504992867332384\n",
      "\t\t召回率 Recall   \t= 0.0033333333333333335\n",
      "TP 4285 P 4800 FP 2294 N 2608\n",
      "测试特征128_31\n",
      "\t\t精确率 Precision\t= 0.5036977474570099\n",
      "\t\t召回率 Recall   \t= 0.8927083333333333\n",
      "TP 2141 P 4800 FP 1190 N 2608\n",
      "测试特征128_32\n",
      "\t\t精确率 Precision\t= 0.49432210124039816\n",
      "\t\t召回率 Recall   \t= 0.44604166666666667\n",
      "TP 671 P 4800 FP 420 N 2608\n",
      "测试特征128_33\n",
      "\t\t精确率 Precision\t= 0.4646794662089535\n",
      "\t\t召回率 Recall   \t= 0.13979166666666668\n",
      "TP 4245 P 4800 FP 2264 N 2608\n",
      "测试特征129_31\n",
      "\t\t精确率 Precision\t= 0.5046439628482973\n",
      "\t\t召回率 Recall   \t= 0.884375\n",
      "TP 2196 P 4800 FP 1227 N 2608\n",
      "测试特征129_32\n",
      "\t\t精确率 Precision\t= 0.4930087266957557\n",
      "\t\t召回率 Recall   \t= 0.4575\n",
      "TP 524 P 4800 FP 312 N 2608\n",
      "测试特征129_33\n",
      "\t\t精确率 Precision\t= 0.4771300248028065\n",
      "\t\t召回率 Recall   \t= 0.10916666666666666\n",
      "TP 4277 P 4800 FP 2289 N 2608\n",
      "测试特征130_31\n",
      "\t\t精确率 Precision\t= 0.5037760568153653\n",
      "\t\t召回率 Recall   \t= 0.8910416666666666\n",
      "TP 1805 P 4800 FP 995 N 2608\n",
      "测试特征130_32\n",
      "\t\t精确率 Precision\t= 0.4963852779160305\n",
      "\t\t召回率 Recall   \t= 0.37604166666666666\n",
      "TP 1322 P 4800 FP 779 N 2608\n",
      "测试特征130_33\n",
      "\t\t精确率 Precision\t= 0.4797255479912553\n",
      "\t\t召回率 Recall   \t= 0.27541666666666664\n",
      "TP 4285 P 4800 FP 2294 N 2608\n",
      "测试特征131_31\n",
      "\t\t精确率 Precision\t= 0.5036977474570099\n",
      "\t\t召回率 Recall   \t= 0.8927083333333333\n",
      "TP 1822 P 4800 FP 998 N 2608\n",
      "测试特征131_32\n",
      "\t\t精确率 Precision\t= 0.49797614296780945\n",
      "\t\t召回率 Recall   \t= 0.37958333333333333\n",
      "TP 1188 P 4800 FP 728 N 2608\n",
      "测试特征131_33\n",
      "\t\t精确率 Precision\t= 0.46995951888633253\n",
      "\t\t召回率 Recall   \t= 0.2475\n",
      "TP 4535 P 4800 FP 2354 N 2608\n",
      "测试特征132_31\n",
      "\t\t精确率 Precision\t= 0.5114172152441703\n",
      "\t\t召回率 Recall   \t= 0.9447916666666667\n",
      "TP 1406 P 4800 FP 966 N 2608\n",
      "测试特征132_32\n",
      "\t\t精确率 Precision\t= 0.4415948267556621\n",
      "\t\t召回率 Recall   \t= 0.29291666666666666\n",
      "TP 121 P 4800 FP 109 N 2608\n",
      "测试特征132_33\n",
      "\t\t精确率 Precision\t= 0.37622799153043507\n",
      "\t\t召回率 Recall   \t= 0.025208333333333333\n",
      "TP 2889 P 4800 FP 1428 N 2608\n",
      "测试特征133_31\n",
      "\t\t精确率 Precision\t= 0.5236331975621229\n",
      "\t\t召回率 Recall   \t= 0.601875\n",
      "TP 2954 P 4800 FP 1786 N 2608\n",
      "测试特征133_32\n",
      "\t\t精确率 Precision\t= 0.4733127429219641\n",
      "\t\t召回率 Recall   \t= 0.6154166666666666\n",
      "TP 293 P 4800 FP 261 N 2608\n",
      "测试特征133_33\n",
      "\t\t精确率 Precision\t= 0.3788622787742248\n",
      "\t\t召回率 Recall   \t= 0.06104166666666667\n",
      "TP 4395 P 4800 FP 2275 N 2608\n",
      "测试特征134_31\n",
      "\t\t精确率 Precision\t= 0.5121114316044564\n",
      "\t\t召回率 Recall   \t= 0.915625\n",
      "TP 1862 P 4800 FP 1196 N 2608\n",
      "测试特征134_32\n",
      "\t\t精确率 Precision\t= 0.4582564554752637\n",
      "\t\t召回率 Recall   \t= 0.3879166666666667\n",
      "TP 164 P 4800 FP 142 N 2608\n",
      "测试特征134_33\n",
      "\t\t精确率 Precision\t= 0.3855651070212888\n",
      "\t\t召回率 Recall   \t= 0.034166666666666665\n",
      "TP 4440 P 4800 FP 2306 N 2608\n",
      "测试特征135_31\n",
      "\t\t精确率 Precision\t= 0.51127500847745\n",
      "\t\t召回率 Recall   \t= 0.925\n",
      "TP 1722 P 4800 FP 1117 N 2608\n",
      "测试特征135_32\n",
      "\t\t精确率 Precision\t= 0.45581744307275585\n",
      "\t\t召回率 Recall   \t= 0.35875\n",
      "TP 151 P 4800 FP 129 N 2608\n",
      "测试特征135_33\n",
      "\t\t精确率 Precision\t= 0.3887511253613002\n",
      "\t\t召回率 Recall   \t= 0.03145833333333333\n"
     ]
    }
   ],
   "source": [
    "for i in range(51,136):\n",
    "    #for j in range(51,136):\n",
    "        j=3\n",
    "        try:\n",
    "            #if(j==3):\n",
    "                get_PR(i,j,1)\n",
    "                get_PR(i,j,2)\n",
    "                get_PR(i,j,3)\n",
    "                #get_PR(i,j,'all')\n",
    "                #get_PR(i,j,12)\n",
    "                #get_PR(i,j,13)\n",
    "                #get_PR(i,j,23)\n",
    "                #get_PR(i,j,123)\n",
    "        except:\n",
    "            print(\"false\")\n",
    "            continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TP 3244 P 5538 FP 1666 N 3871\n",
      "测试特征57_31\n",
      "\t\t精确率 Precision\t= 0.5764607439131921\n",
      "\t\t召回率 Recall   \t= 0.5857710364752619\n",
      "TP 2431 P 5538 FP 2186 N 3871\n",
      "测试特征57_32\n",
      "\t\t精确率 Precision\t= 0.437358053498462\n",
      "\t\t召回率 Recall   \t= 0.43896713615023475\n",
      "TP 172 P 5538 FP 160 N 3871\n",
      "\t\t精确率 Precision\t= 0.4290324326692837\n",
      "\t\t召回率 Recall   \t= 0.031058143734200072\n",
      "TP 172 P 5538 FP 160 N 3871\n",
      "\t\t精确率 Precision\t= 0.4290324326692837\n",
      "\t\t召回率 Recall   \t= 0.031058143734200072\n"
     ]
    }
   ],
   "source": [
    "#特征取交集测试\n",
    "get_PR(57,3,1)\n",
    "get_PR(57,3,2)\n",
    "import pandas as pd\n",
    "dataset = pd.read_csv(open('/data/csv/label_eventsV1.csv','r',encoding = 'gb18030'))#读取总标签数据\n",
    "user_index=['user_name']#初始化一个等待补全的names\n",
    "#print(cols.shape[0]-1)\n",
    "for i in range(1,3):\n",
    "        user_index.append(str(i))\n",
    "user_index.append('count')\n",
    "user_index.append('now')\n",
    "result_1=pd.read_csv(\"/data/jupyter_root/dcube_data/feature57/block_1.tuples\",sep=',',names=user_index)\n",
    "\n",
    "#user_index.pop()\n",
    "result_2=pd.read_csv(\"/data/jupyter_root/dcube_data/feature57/block_2.tuples\",sep=',',names=user_index)\n",
    "names=set(result_1['user_name'].drop_duplicates().values)&set(result_2['user_name'].drop_duplicates().values)\n",
    "data = dataset[dataset['user_name'].isin(names)][['user_name','label']]#预测出坏用户的真实标签分布\n",
    "data = data.drop_duplicates()\n",
    "\n",
    "#user_index.append('now')\n",
    "raw_result=pd.read_csv(\"/data/jupyter_root/dcube_data/feature57.txt\",sep=',',names=user_index)#读取全部的原始数据，并给上names\n",
    "raw_names = raw_result['user_name'].drop_duplicates()#原始数据中用户的用户列表\n",
    "#print(raw_names)\n",
    "raw_data = dataset[dataset['user_name'].isin(raw_names)][['user_name','label']]#原始数据中用户的真实标签分布\n",
    "raw_data = raw_data.drop_duplicates()#去重\n",
    "\n",
    "TP=data.label.sum()\n",
    "P=raw_data.label.sum()\n",
    "FP=data.label.count()-data.label.sum()\n",
    "N=raw_data.label.count()-raw_data.label.sum()\n",
    "Precision = (TP/P)/(TP/P+FP/N) #精确率计算\n",
    "\n",
    "\n",
    "    #data_label_1 = dataset[dataset['label']==1][['user_name','label']] #原数据中label为1的坏用户\n",
    "    #data_label_1 = data_label_1.drop_duplicates()#去重\n",
    "Recall = data.label.sum()/raw_data.label.sum() # 召回率计算\n",
    "print(\"TP\",TP,\"P\",P,\"FP\",FP,\"N\",N)\n",
    "print('\\t\\t精确率 Precision\\t= '+str(Precision))\n",
    "print('\\t\\t召回率 Recall   \\t= '+str(Recall))\n",
    "#user_index.pop()\n",
    "\n",
    "raw_result=pd.read_csv(\"/data/jupyter_root/dcube_data/feature57.txt\",sep=',',names=user_index)#读取全部的原始数据，并给上names\n",
    "raw_names = raw_result['user_name'].drop_duplicates()#原始数据中用户的用户列表\n",
    "#print(raw_names)\n",
    "raw_data = dataset[dataset['user_name'].isin(raw_names)][['user_name','label']]#原始数据中坏用户的真实标签分布\n",
    "raw_data = raw_data.drop_duplicates()#去重\n",
    "\n",
    "TP=data.label.sum()\n",
    "P=raw_data.label.sum()\n",
    "FP=data.label.count()-data.label.sum()\n",
    "N=raw_data.label.count()-raw_data.label.sum()\n",
    "Precision = (TP/P)/(TP/P+FP/N) #精确率计算\n",
    "\n",
    "    #data_label_1 = dataset[dataset['label']==1][['user_name','label']] #原数据中label为1的坏用户\n",
    "    #data_label_1 = data_label_1.drop_duplicates()#去重\n",
    "Recall = data.label.sum()/raw_data.label.sum() # 召回率计算\n",
    "print(\"TP\",TP,\"P\",P,\"FP\",FP,\"N\",N)\n",
    "print('\\t\\t精确率 Precision\\t= '+str(Precision))\n",
    "print('\\t\\t召回率 Recall   \\t= '+str(Recall))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 精确率Precision的计算"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 召回率Recall的计算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Feature_combination</th>\n",
       "      <th>Standard</th>\n",
       "      <th>Poly</th>\n",
       "      <th>user_name_dic</th>\n",
       "      <th>user_name_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>feature1</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>feature2</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>feature3</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature4</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>feature5</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>feature6</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>feature7</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>feature8</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>feature9</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>feature10</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>feature11</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>feature12</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>feature13</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>feature14</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>feature15</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>feature16</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>feature17</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>feature18</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>feature19</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>feature20</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>feature21</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>feature22</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>feature23</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>feature24</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>feature25</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>feature26</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>feature27</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>feature28</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>feature29</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>feature30</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>feature31</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>feature32</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>feature33</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>feature34</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>feature35</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>feature36</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>feature37</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>feature38</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>feature39</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>feature40</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>feature41</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>feature42</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>feature43</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>feature44</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>feature45</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>feature46</td>\n",
       "      <td>['user_name']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>feature47</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>feature48</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>feature49</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>feature50</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>feature51</td>\n",
       "      <td>['user_name', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>feature52</td>\n",
       "      <td>['user_name', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>feature53</td>\n",
       "      <td>['user_name', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>feature54</td>\n",
       "      <td>['user_name', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>feature55</td>\n",
       "      <td>['user_name', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>feature56</td>\n",
       "      <td>['user_name', 'user_agent', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>feature57</td>\n",
       "      <td>['user_name', 'user_agent', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>feature58</td>\n",
       "      <td>['user_name', 'user_agent', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>feature59</td>\n",
       "      <td>['user_name', 'user_agent', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>feature60</td>\n",
       "      <td>['user_name', 'os_version', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>feature61</td>\n",
       "      <td>['user_name', 'os_version', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>feature62</td>\n",
       "      <td>['user_name', 'os_version', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>feature63</td>\n",
       "      <td>['user_name', 'os_version', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>feature64</td>\n",
       "      <td>['user_name', 'ip_1', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>feature65</td>\n",
       "      <td>['user_name', 'ip_1', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>feature66</td>\n",
       "      <td>['user_name', 'ip_1', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>feature67</td>\n",
       "      <td>['user_name', 'ip_1', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>feature68</td>\n",
       "      <td>['user_name', 'ip_12', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>feature69</td>\n",
       "      <td>['user_name', 'ip_12', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>feature70</td>\n",
       "      <td>['user_name', 'ip_12', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>feature71</td>\n",
       "      <td>['user_name', 'ip_12', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>feature72</td>\n",
       "      <td>['user_name', 'ip_123', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>feature73</td>\n",
       "      <td>['user_name', 'ip_123', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>feature74</td>\n",
       "      <td>['user_name', 'ip_123', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>feature75</td>\n",
       "      <td>['user_name', 'ip_123', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>feature76</td>\n",
       "      <td>['user_name', 'ip_1234', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>feature77</td>\n",
       "      <td>['user_name', 'ip_1234', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>feature78</td>\n",
       "      <td>['user_name', 'ip_1234', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>feature79</td>\n",
       "      <td>['user_name', 'ip_1234', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>feature80</td>\n",
       "      <td>['user_name', 'ip_city', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>feature81</td>\n",
       "      <td>['user_name', 'ip_city', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>feature82</td>\n",
       "      <td>['user_name', 'ip_city', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>feature83</td>\n",
       "      <td>['user_name', 'ip_city', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>feature84</td>\n",
       "      <td>['user_name', 'resource_owner', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>feature85</td>\n",
       "      <td>['user_name', 'resource_owner', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>feature86</td>\n",
       "      <td>['user_name', 'resource_owner', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>feature87</td>\n",
       "      <td>['user_name', 'resource_owner', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>feature88</td>\n",
       "      <td>['user_name', 'resource_type', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>feature89</td>\n",
       "      <td>['user_name', 'resource_type', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>feature90</td>\n",
       "      <td>['user_name', 'resource_type', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>feature91</td>\n",
       "      <td>['user_name', 'resource_type', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>feature92</td>\n",
       "      <td>['user_name', 'resource_category', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>feature93</td>\n",
       "      <td>['user_name', 'resource_category', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>feature94</td>\n",
       "      <td>['user_name', 'resource_category', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>feature95</td>\n",
       "      <td>['user_name', 'resource_category', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>feature96</td>\n",
       "      <td>['user_name', 'user_agent', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>feature97</td>\n",
       "      <td>['user_name', 'user_agent', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>feature98</td>\n",
       "      <td>['user_name', 'user_agent', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>feature99</td>\n",
       "      <td>['user_name', 'user_agent', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>feature100</td>\n",
       "      <td>['user_name', 'os_version', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>feature101</td>\n",
       "      <td>['user_name', 'os_version', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>feature102</td>\n",
       "      <td>['user_name', 'os_version', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>feature103</td>\n",
       "      <td>['user_name', 'os_version', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>feature104</td>\n",
       "      <td>['user_name', 'ip_1', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>feature105</td>\n",
       "      <td>['user_name', 'ip_1', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>feature106</td>\n",
       "      <td>['user_name', 'ip_1', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>feature107</td>\n",
       "      <td>['user_name', 'ip_1', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>feature108</td>\n",
       "      <td>['user_name', 'ip_12', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>feature109</td>\n",
       "      <td>['user_name', 'ip_12', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>feature110</td>\n",
       "      <td>['user_name', 'ip_12', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>feature111</td>\n",
       "      <td>['user_name', 'ip_12', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>feature112</td>\n",
       "      <td>['user_name', 'ip_123', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>feature113</td>\n",
       "      <td>['user_name', 'ip_123', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>feature114</td>\n",
       "      <td>['user_name', 'ip_123', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>feature115</td>\n",
       "      <td>['user_name', 'ip_123', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>feature116</td>\n",
       "      <td>['user_name', 'ip_1234', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>feature117</td>\n",
       "      <td>['user_name', 'ip_1234', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>feature118</td>\n",
       "      <td>['user_name', 'ip_1234', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>feature119</td>\n",
       "      <td>['user_name', 'ip_1234', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>feature120</td>\n",
       "      <td>['user_name', 'ip_city', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>feature121</td>\n",
       "      <td>['user_name', 'ip_city', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>feature122</td>\n",
       "      <td>['user_name', 'ip_city', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>feature123</td>\n",
       "      <td>['user_name', 'ip_city', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>feature124</td>\n",
       "      <td>['user_name', 'resource_owner', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>feature125</td>\n",
       "      <td>['user_name', 'resource_owner', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>feature126</td>\n",
       "      <td>['user_name', 'resource_owner', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>feature127</td>\n",
       "      <td>['user_name', 'resource_owner', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>feature128</td>\n",
       "      <td>['user_name', 'resource_type', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>feature129</td>\n",
       "      <td>['user_name', 'resource_type', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>feature130</td>\n",
       "      <td>['user_name', 'resource_type', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>feature131</td>\n",
       "      <td>['user_name', 'resource_type', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>feature132</td>\n",
       "      <td>['user_name', 'resource_category', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>feature133</td>\n",
       "      <td>['user_name', 'resource_category', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>feature134</td>\n",
       "      <td>['user_name', 'resource_category', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>feature135</td>\n",
       "      <td>['user_name', 'resource_category', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>7408</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0  \\\n",
       "0      feature1   \n",
       "1      feature2   \n",
       "2      feature3   \n",
       "3      feature4   \n",
       "4      feature5   \n",
       "5      feature6   \n",
       "6      feature7   \n",
       "7      feature8   \n",
       "8      feature9   \n",
       "9     feature10   \n",
       "10    feature11   \n",
       "11    feature12   \n",
       "12    feature13   \n",
       "13    feature14   \n",
       "14    feature15   \n",
       "15    feature16   \n",
       "16    feature17   \n",
       "17    feature18   \n",
       "18    feature19   \n",
       "19    feature20   \n",
       "20    feature21   \n",
       "21    feature22   \n",
       "22    feature23   \n",
       "23    feature24   \n",
       "24    feature25   \n",
       "25    feature26   \n",
       "26    feature27   \n",
       "27    feature28   \n",
       "28    feature29   \n",
       "29    feature30   \n",
       "30    feature31   \n",
       "31    feature32   \n",
       "32    feature33   \n",
       "33    feature34   \n",
       "34    feature35   \n",
       "35    feature36   \n",
       "36    feature37   \n",
       "37    feature38   \n",
       "38    feature39   \n",
       "39    feature40   \n",
       "40    feature41   \n",
       "41    feature42   \n",
       "42    feature43   \n",
       "43    feature44   \n",
       "44    feature45   \n",
       "45    feature46   \n",
       "46    feature47   \n",
       "47    feature48   \n",
       "48    feature49   \n",
       "49    feature50   \n",
       "50    feature51   \n",
       "51    feature52   \n",
       "52    feature53   \n",
       "53    feature54   \n",
       "54    feature55   \n",
       "55    feature56   \n",
       "56    feature57   \n",
       "57    feature58   \n",
       "58    feature59   \n",
       "59    feature60   \n",
       "60    feature61   \n",
       "61    feature62   \n",
       "62    feature63   \n",
       "63    feature64   \n",
       "64    feature65   \n",
       "65    feature66   \n",
       "66    feature67   \n",
       "67    feature68   \n",
       "68    feature69   \n",
       "69    feature70   \n",
       "70    feature71   \n",
       "71    feature72   \n",
       "72    feature73   \n",
       "73    feature74   \n",
       "74    feature75   \n",
       "75    feature76   \n",
       "76    feature77   \n",
       "77    feature78   \n",
       "78    feature79   \n",
       "79    feature80   \n",
       "80    feature81   \n",
       "81    feature82   \n",
       "82    feature83   \n",
       "83    feature84   \n",
       "84    feature85   \n",
       "85    feature86   \n",
       "86    feature87   \n",
       "87    feature88   \n",
       "88    feature89   \n",
       "89    feature90   \n",
       "90    feature91   \n",
       "91    feature92   \n",
       "92    feature93   \n",
       "93    feature94   \n",
       "94    feature95   \n",
       "95    feature96   \n",
       "96    feature97   \n",
       "97    feature98   \n",
       "98    feature99   \n",
       "99   feature100   \n",
       "100  feature101   \n",
       "101  feature102   \n",
       "102  feature103   \n",
       "103  feature104   \n",
       "104  feature105   \n",
       "105  feature106   \n",
       "106  feature107   \n",
       "107  feature108   \n",
       "108  feature109   \n",
       "109  feature110   \n",
       "110  feature111   \n",
       "111  feature112   \n",
       "112  feature113   \n",
       "113  feature114   \n",
       "114  feature115   \n",
       "115  feature116   \n",
       "116  feature117   \n",
       "117  feature118   \n",
       "118  feature119   \n",
       "119  feature120   \n",
       "120  feature121   \n",
       "121  feature122   \n",
       "122  feature123   \n",
       "123  feature124   \n",
       "124  feature125   \n",
       "125  feature126   \n",
       "126  feature127   \n",
       "127  feature128   \n",
       "128  feature129   \n",
       "129  feature130   \n",
       "130  feature131   \n",
       "131  feature132   \n",
       "132  feature133   \n",
       "133  feature134   \n",
       "134  feature135   \n",
       "\n",
       "                                                      Feature_combination  \\\n",
       "0                                                           ['user_name']   \n",
       "1                                         ['user_name', 'time_stamp_day']   \n",
       "2                                        ['user_name', 'time_stamp_hour']   \n",
       "3                                       ['user_name', 'time_stamp_3hour']   \n",
       "4                                       ['user_name', 'time_stamp_6hour']   \n",
       "5                                                           ['user_name']   \n",
       "6                                         ['user_name', 'time_stamp_day']   \n",
       "7                                        ['user_name', 'time_stamp_hour']   \n",
       "8                                       ['user_name', 'time_stamp_3hour']   \n",
       "9                                       ['user_name', 'time_stamp_6hour']   \n",
       "10                                                          ['user_name']   \n",
       "11                                        ['user_name', 'time_stamp_day']   \n",
       "12                                       ['user_name', 'time_stamp_hour']   \n",
       "13                                      ['user_name', 'time_stamp_3hour']   \n",
       "14                                      ['user_name', 'time_stamp_6hour']   \n",
       "15                                                          ['user_name']   \n",
       "16                                        ['user_name', 'time_stamp_day']   \n",
       "17                                       ['user_name', 'time_stamp_hour']   \n",
       "18                                      ['user_name', 'time_stamp_3hour']   \n",
       "19                                      ['user_name', 'time_stamp_6hour']   \n",
       "20                                                          ['user_name']   \n",
       "21                                        ['user_name', 'time_stamp_day']   \n",
       "22                                       ['user_name', 'time_stamp_hour']   \n",
       "23                                      ['user_name', 'time_stamp_3hour']   \n",
       "24                                      ['user_name', 'time_stamp_6hour']   \n",
       "25                                                          ['user_name']   \n",
       "26                                        ['user_name', 'time_stamp_day']   \n",
       "27                                       ['user_name', 'time_stamp_hour']   \n",
       "28                                      ['user_name', 'time_stamp_3hour']   \n",
       "29                                      ['user_name', 'time_stamp_6hour']   \n",
       "30                                                          ['user_name']   \n",
       "31                                        ['user_name', 'time_stamp_day']   \n",
       "32                                       ['user_name', 'time_stamp_hour']   \n",
       "33                                      ['user_name', 'time_stamp_3hour']   \n",
       "34                                      ['user_name', 'time_stamp_6hour']   \n",
       "35                                                          ['user_name']   \n",
       "36                                        ['user_name', 'time_stamp_day']   \n",
       "37                                       ['user_name', 'time_stamp_hour']   \n",
       "38                                      ['user_name', 'time_stamp_3hour']   \n",
       "39                                      ['user_name', 'time_stamp_6hour']   \n",
       "40                                                          ['user_name']   \n",
       "41                                        ['user_name', 'time_stamp_day']   \n",
       "42                                       ['user_name', 'time_stamp_hour']   \n",
       "43                                      ['user_name', 'time_stamp_3hour']   \n",
       "44                                      ['user_name', 'time_stamp_6hour']   \n",
       "45                                                          ['user_name']   \n",
       "46                                        ['user_name', 'time_stamp_day']   \n",
       "47                                       ['user_name', 'time_stamp_hour']   \n",
       "48                                      ['user_name', 'time_stamp_3hour']   \n",
       "49                                      ['user_name', 'time_stamp_6hour']   \n",
       "50                                            ['user_name', 'event_type']   \n",
       "51                                        ['user_name', 'time_stamp_day']   \n",
       "52                                       ['user_name', 'time_stamp_hour']   \n",
       "53                                      ['user_name', 'time_stamp_3hour']   \n",
       "54                                      ['user_name', 'time_stamp_6hour']   \n",
       "55                          ['user_name', 'user_agent', 'time_stamp_day']   \n",
       "56                         ['user_name', 'user_agent', 'time_stamp_hour']   \n",
       "57                        ['user_name', 'user_agent', 'time_stamp_3hour']   \n",
       "58                        ['user_name', 'user_agent', 'time_stamp_6hour']   \n",
       "59                          ['user_name', 'os_version', 'time_stamp_day']   \n",
       "60                         ['user_name', 'os_version', 'time_stamp_hour']   \n",
       "61                        ['user_name', 'os_version', 'time_stamp_3hour']   \n",
       "62                        ['user_name', 'os_version', 'time_stamp_6hour']   \n",
       "63                                ['user_name', 'ip_1', 'time_stamp_day']   \n",
       "64                               ['user_name', 'ip_1', 'time_stamp_hour']   \n",
       "65                              ['user_name', 'ip_1', 'time_stamp_3hour']   \n",
       "66                              ['user_name', 'ip_1', 'time_stamp_6hour']   \n",
       "67                               ['user_name', 'ip_12', 'time_stamp_day']   \n",
       "68                              ['user_name', 'ip_12', 'time_stamp_hour']   \n",
       "69                             ['user_name', 'ip_12', 'time_stamp_3hour']   \n",
       "70                             ['user_name', 'ip_12', 'time_stamp_6hour']   \n",
       "71                              ['user_name', 'ip_123', 'time_stamp_day']   \n",
       "72                             ['user_name', 'ip_123', 'time_stamp_hour']   \n",
       "73                            ['user_name', 'ip_123', 'time_stamp_3hour']   \n",
       "74                            ['user_name', 'ip_123', 'time_stamp_6hour']   \n",
       "75                             ['user_name', 'ip_1234', 'time_stamp_day']   \n",
       "76                            ['user_name', 'ip_1234', 'time_stamp_hour']   \n",
       "77                           ['user_name', 'ip_1234', 'time_stamp_3hour']   \n",
       "78                           ['user_name', 'ip_1234', 'time_stamp_6hour']   \n",
       "79                             ['user_name', 'ip_city', 'time_stamp_day']   \n",
       "80                            ['user_name', 'ip_city', 'time_stamp_hour']   \n",
       "81                           ['user_name', 'ip_city', 'time_stamp_3hour']   \n",
       "82                           ['user_name', 'ip_city', 'time_stamp_6hour']   \n",
       "83                      ['user_name', 'resource_owner', 'time_stamp_day']   \n",
       "84                     ['user_name', 'resource_owner', 'time_stamp_hour']   \n",
       "85                    ['user_name', 'resource_owner', 'time_stamp_3hour']   \n",
       "86                    ['user_name', 'resource_owner', 'time_stamp_6hour']   \n",
       "87                       ['user_name', 'resource_type', 'time_stamp_day']   \n",
       "88                      ['user_name', 'resource_type', 'time_stamp_hour']   \n",
       "89                     ['user_name', 'resource_type', 'time_stamp_3hour']   \n",
       "90                     ['user_name', 'resource_type', 'time_stamp_6hour']   \n",
       "91                   ['user_name', 'resource_category', 'time_stamp_day']   \n",
       "92                  ['user_name', 'resource_category', 'time_stamp_hour']   \n",
       "93                 ['user_name', 'resource_category', 'time_stamp_3hour']   \n",
       "94                 ['user_name', 'resource_category', 'time_stamp_6hour']   \n",
       "95            ['user_name', 'user_agent', 'time_stamp_day', 'event_type']   \n",
       "96           ['user_name', 'user_agent', 'time_stamp_hour', 'event_type']   \n",
       "97          ['user_name', 'user_agent', 'time_stamp_3hour', 'event_type']   \n",
       "98          ['user_name', 'user_agent', 'time_stamp_6hour', 'event_type']   \n",
       "99            ['user_name', 'os_version', 'time_stamp_day', 'event_type']   \n",
       "100          ['user_name', 'os_version', 'time_stamp_hour', 'event_type']   \n",
       "101         ['user_name', 'os_version', 'time_stamp_3hour', 'event_type']   \n",
       "102         ['user_name', 'os_version', 'time_stamp_6hour', 'event_type']   \n",
       "103                 ['user_name', 'ip_1', 'time_stamp_day', 'event_type']   \n",
       "104                ['user_name', 'ip_1', 'time_stamp_hour', 'event_type']   \n",
       "105               ['user_name', 'ip_1', 'time_stamp_3hour', 'event_type']   \n",
       "106               ['user_name', 'ip_1', 'time_stamp_6hour', 'event_type']   \n",
       "107                ['user_name', 'ip_12', 'time_stamp_day', 'event_type']   \n",
       "108               ['user_name', 'ip_12', 'time_stamp_hour', 'event_type']   \n",
       "109              ['user_name', 'ip_12', 'time_stamp_3hour', 'event_type']   \n",
       "110              ['user_name', 'ip_12', 'time_stamp_6hour', 'event_type']   \n",
       "111               ['user_name', 'ip_123', 'time_stamp_day', 'event_type']   \n",
       "112              ['user_name', 'ip_123', 'time_stamp_hour', 'event_type']   \n",
       "113             ['user_name', 'ip_123', 'time_stamp_3hour', 'event_type']   \n",
       "114             ['user_name', 'ip_123', 'time_stamp_6hour', 'event_type']   \n",
       "115              ['user_name', 'ip_1234', 'time_stamp_day', 'event_type']   \n",
       "116             ['user_name', 'ip_1234', 'time_stamp_hour', 'event_type']   \n",
       "117            ['user_name', 'ip_1234', 'time_stamp_3hour', 'event_type']   \n",
       "118            ['user_name', 'ip_1234', 'time_stamp_6hour', 'event_type']   \n",
       "119              ['user_name', 'ip_city', 'time_stamp_day', 'event_type']   \n",
       "120             ['user_name', 'ip_city', 'time_stamp_hour', 'event_type']   \n",
       "121            ['user_name', 'ip_city', 'time_stamp_3hour', 'event_type']   \n",
       "122            ['user_name', 'ip_city', 'time_stamp_6hour', 'event_type']   \n",
       "123       ['user_name', 'resource_owner', 'time_stamp_day', 'event_type']   \n",
       "124      ['user_name', 'resource_owner', 'time_stamp_hour', 'event_type']   \n",
       "125     ['user_name', 'resource_owner', 'time_stamp_3hour', 'event_type']   \n",
       "126     ['user_name', 'resource_owner', 'time_stamp_6hour', 'event_type']   \n",
       "127        ['user_name', 'resource_type', 'time_stamp_day', 'event_type']   \n",
       "128       ['user_name', 'resource_type', 'time_stamp_hour', 'event_type']   \n",
       "129      ['user_name', 'resource_type', 'time_stamp_3hour', 'event_type']   \n",
       "130      ['user_name', 'resource_type', 'time_stamp_6hour', 'event_type']   \n",
       "131    ['user_name', 'resource_category', 'time_stamp_day', 'event_type']   \n",
       "132   ['user_name', 'resource_category', 'time_stamp_hour', 'event_type']   \n",
       "133  ['user_name', 'resource_category', 'time_stamp_3hour', 'event_type']   \n",
       "134  ['user_name', 'resource_category', 'time_stamp_6hour', 'event_type']   \n",
       "\n",
       "              Standard     Poly  \\\n",
       "0           user_agent  nunique   \n",
       "1           user_agent  nunique   \n",
       "2           user_agent  nunique   \n",
       "3           user_agent  nunique   \n",
       "4           user_agent  nunique   \n",
       "5           os_version  nunique   \n",
       "6           os_version  nunique   \n",
       "7           os_version  nunique   \n",
       "8           os_version  nunique   \n",
       "9           os_version  nunique   \n",
       "10                ip_1  nunique   \n",
       "11                ip_1  nunique   \n",
       "12                ip_1  nunique   \n",
       "13                ip_1  nunique   \n",
       "14                ip_1  nunique   \n",
       "15               ip_12  nunique   \n",
       "16               ip_12  nunique   \n",
       "17               ip_12  nunique   \n",
       "18               ip_12  nunique   \n",
       "19               ip_12  nunique   \n",
       "20              ip_123  nunique   \n",
       "21              ip_123  nunique   \n",
       "22              ip_123  nunique   \n",
       "23              ip_123  nunique   \n",
       "24              ip_123  nunique   \n",
       "25             ip_1234  nunique   \n",
       "26             ip_1234  nunique   \n",
       "27             ip_1234  nunique   \n",
       "28             ip_1234  nunique   \n",
       "29             ip_1234  nunique   \n",
       "30             ip_city  nunique   \n",
       "31             ip_city  nunique   \n",
       "32             ip_city  nunique   \n",
       "33             ip_city  nunique   \n",
       "34             ip_city  nunique   \n",
       "35      resource_owner  nunique   \n",
       "36      resource_owner  nunique   \n",
       "37      resource_owner  nunique   \n",
       "38      resource_owner  nunique   \n",
       "39      resource_owner  nunique   \n",
       "40       resource_type  nunique   \n",
       "41       resource_type  nunique   \n",
       "42       resource_type  nunique   \n",
       "43       resource_type  nunique   \n",
       "44       resource_type  nunique   \n",
       "45   resource_category  nunique   \n",
       "46   resource_category  nunique   \n",
       "47   resource_category  nunique   \n",
       "48   resource_category  nunique   \n",
       "49   resource_category  nunique   \n",
       "50               index    count   \n",
       "51               index    count   \n",
       "52               index    count   \n",
       "53               index    count   \n",
       "54               index    count   \n",
       "55               index    count   \n",
       "56               index    count   \n",
       "57               index    count   \n",
       "58               index    count   \n",
       "59               index    count   \n",
       "60               index    count   \n",
       "61               index    count   \n",
       "62               index    count   \n",
       "63               index    count   \n",
       "64               index    count   \n",
       "65               index    count   \n",
       "66               index    count   \n",
       "67               index    count   \n",
       "68               index    count   \n",
       "69               index    count   \n",
       "70               index    count   \n",
       "71               index    count   \n",
       "72               index    count   \n",
       "73               index    count   \n",
       "74               index    count   \n",
       "75               index    count   \n",
       "76               index    count   \n",
       "77               index    count   \n",
       "78               index    count   \n",
       "79               index    count   \n",
       "80               index    count   \n",
       "81               index    count   \n",
       "82               index    count   \n",
       "83               index    count   \n",
       "84               index    count   \n",
       "85               index    count   \n",
       "86               index    count   \n",
       "87               index    count   \n",
       "88               index    count   \n",
       "89               index    count   \n",
       "90               index    count   \n",
       "91               index    count   \n",
       "92               index    count   \n",
       "93               index    count   \n",
       "94               index    count   \n",
       "95               index    count   \n",
       "96               index    count   \n",
       "97               index    count   \n",
       "98               index    count   \n",
       "99               index    count   \n",
       "100              index    count   \n",
       "101              index    count   \n",
       "102              index    count   \n",
       "103              index    count   \n",
       "104              index    count   \n",
       "105              index    count   \n",
       "106              index    count   \n",
       "107              index    count   \n",
       "108              index    count   \n",
       "109              index    count   \n",
       "110              index    count   \n",
       "111              index    count   \n",
       "112              index    count   \n",
       "113              index    count   \n",
       "114              index    count   \n",
       "115              index    count   \n",
       "116              index    count   \n",
       "117              index    count   \n",
       "118              index    count   \n",
       "119              index    count   \n",
       "120              index    count   \n",
       "121              index    count   \n",
       "122              index    count   \n",
       "123              index    count   \n",
       "124              index    count   \n",
       "125              index    count   \n",
       "126              index    count   \n",
       "127              index    count   \n",
       "128              index    count   \n",
       "129              index    count   \n",
       "130              index    count   \n",
       "131              index    count   \n",
       "132              index    count   \n",
       "133              index    count   \n",
       "134              index    count   \n",
       "\n",
       "                                                                                           user_name_dic  \\\n",
       "0    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "1    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "2    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "3    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "4    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "5    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "6    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "7    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "8    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "9    {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "10   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "11   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "12   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "13   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "14   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "15   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "16   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "17   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "18   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "19   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "20   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "21   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "22   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "23   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "24   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "25   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "26   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "27   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "28   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "29   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "30   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "31   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "32   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "33   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "34   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "35   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "36   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "37   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "38   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "39   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "40   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "41   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "42   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "43   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "44   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "45   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "46   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "47   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "48   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "49   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "50   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "51   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "52   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "53   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "54   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "55   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "56   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "57   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "58   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "59   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "60   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "61   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "62   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "63   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "64   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "65   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "66   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "67   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "68   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "69   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "70   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "71   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "72   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "73   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "74   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "75   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "76   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "77   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "78   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "79   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "80   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "81   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "82   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "83   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "84   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "85   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "86   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "87   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "88   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "89   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "90   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "91   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "92   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "93   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "94   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "95   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "96   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "97   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "98   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "99   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "100  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "101  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "102  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "103  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "104  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "105  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "106  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "107  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "108  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "109  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "110  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "111  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "112  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "113  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "114  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "115  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "116  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "117  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "118  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "119  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "120  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "121  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "122  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "123  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "124  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "125  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "126  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
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       "\n",
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       "132           7408  \n",
       "133           7408  \n",
       "134           7408  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('max_row',200) \n",
    "pd.set_option('display.max_colwidth', 100)\n",
    "pd.read_csv(\"/data/jupyter_root/dcube_data/have_name/feature_list.csv\",sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/data/jupyter_root/LSK'"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " 1513120,\n",
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       " 1546110,\n",
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       " 1546143,\n",
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       " 235444,\n",
       " 104379,\n",
       " 104381,\n",
       " 1447870,\n",
       " 1578947,\n",
       " ...}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "user_index=['user_name']#初始化一个等待补全的names\n",
    "#print(cols.shape[0]-1)\n",
    "for i in range(1,3):\n",
    "        user_index.append(str(i))\n",
    "user_index.append('count')\n",
    "result_1=pd.read_csv(\"./block12.txt\",sep=',',names=user_index)\n",
    "result_2=pd.read_csv(\"./block13.txt\",sep=',',names=user_index)\n",
    "set(result_1['user_name'].drop_duplicates().values)&set(result_2['user_name'].drop_duplicates().values)\n",
    "fet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Feature_combination</th>\n",
       "      <th>Standard</th>\n",
       "      <th>Poly</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>feature1</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>feature2</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>feature3</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature4</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>user_agent</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>feature5</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>feature6</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>feature7</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>feature8</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>os_version</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>feature9</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>feature10</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>feature11</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>feature12</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>ip_1</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>feature13</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>feature14</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>feature15</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>feature16</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>ip_12</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>feature17</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>feature18</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>feature19</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>feature20</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>ip_123</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>feature21</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>feature22</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>feature23</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>feature24</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>ip_1234</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>feature25</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>feature26</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>feature27</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>feature28</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>ip_city</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>feature29</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>feature30</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>feature31</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>feature32</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>resource_owner</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>feature33</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>feature34</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>feature35</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>feature36</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>resource_type</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>feature37</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>feature38</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>feature39</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>feature40</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>resource_category</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>feature41</td>\n",
       "      <td>['event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>feature42</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>feature43</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>feature44</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>feature45</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>feature46</td>\n",
       "      <td>['user_agent', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>feature47</td>\n",
       "      <td>['user_agent', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>feature48</td>\n",
       "      <td>['user_agent', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>feature49</td>\n",
       "      <td>['user_agent', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>feature50</td>\n",
       "      <td>['os_version', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>feature51</td>\n",
       "      <td>['os_version', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>feature52</td>\n",
       "      <td>['os_version', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>feature53</td>\n",
       "      <td>['os_version', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>feature54</td>\n",
       "      <td>['ip_1', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>feature55</td>\n",
       "      <td>['ip_1', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>feature56</td>\n",
       "      <td>['ip_1', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>feature57</td>\n",
       "      <td>['ip_1', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>feature58</td>\n",
       "      <td>['ip_12', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>feature59</td>\n",
       "      <td>['ip_12', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>feature60</td>\n",
       "      <td>['ip_12', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>feature61</td>\n",
       "      <td>['ip_12', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>feature62</td>\n",
       "      <td>['ip_123', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>feature63</td>\n",
       "      <td>['ip_123', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>feature64</td>\n",
       "      <td>['ip_123', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>feature65</td>\n",
       "      <td>['ip_123', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>feature66</td>\n",
       "      <td>['ip_1234', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>feature67</td>\n",
       "      <td>['ip_1234', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>feature68</td>\n",
       "      <td>['ip_1234', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>feature69</td>\n",
       "      <td>['ip_1234', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>feature70</td>\n",
       "      <td>['ip_city', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>feature71</td>\n",
       "      <td>['ip_city', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>feature72</td>\n",
       "      <td>['ip_city', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>feature73</td>\n",
       "      <td>['ip_city', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>feature74</td>\n",
       "      <td>['resource_owner', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>feature75</td>\n",
       "      <td>['resource_owner', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>feature76</td>\n",
       "      <td>['resource_owner', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>feature77</td>\n",
       "      <td>['resource_owner', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>feature78</td>\n",
       "      <td>['resource_type', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>feature79</td>\n",
       "      <td>['resource_type', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>feature80</td>\n",
       "      <td>['resource_type', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>feature81</td>\n",
       "      <td>['resource_type', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>feature82</td>\n",
       "      <td>['resource_category', 'time_stamp_day']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>feature83</td>\n",
       "      <td>['resource_category', 'time_stamp_hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>feature84</td>\n",
       "      <td>['resource_category', 'time_stamp_3hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>feature85</td>\n",
       "      <td>['resource_category', 'time_stamp_6hour']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>feature86</td>\n",
       "      <td>['user_agent', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>feature87</td>\n",
       "      <td>['user_agent', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>feature88</td>\n",
       "      <td>['user_agent', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>feature89</td>\n",
       "      <td>['user_agent', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>feature90</td>\n",
       "      <td>['os_version', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>feature91</td>\n",
       "      <td>['os_version', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>feature92</td>\n",
       "      <td>['os_version', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>feature93</td>\n",
       "      <td>['os_version', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>feature94</td>\n",
       "      <td>['ip_1', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>feature95</td>\n",
       "      <td>['ip_1', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>feature96</td>\n",
       "      <td>['ip_1', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>feature97</td>\n",
       "      <td>['ip_1', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>feature98</td>\n",
       "      <td>['ip_12', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>feature99</td>\n",
       "      <td>['ip_12', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>feature100</td>\n",
       "      <td>['ip_12', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>feature101</td>\n",
       "      <td>['ip_12', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>feature102</td>\n",
       "      <td>['ip_123', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>feature103</td>\n",
       "      <td>['ip_123', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>feature104</td>\n",
       "      <td>['ip_123', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>feature105</td>\n",
       "      <td>['ip_123', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>feature106</td>\n",
       "      <td>['ip_1234', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>feature107</td>\n",
       "      <td>['ip_1234', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>feature108</td>\n",
       "      <td>['ip_1234', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>feature109</td>\n",
       "      <td>['ip_1234', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>feature110</td>\n",
       "      <td>['ip_city', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>feature111</td>\n",
       "      <td>['ip_city', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>feature112</td>\n",
       "      <td>['ip_city', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>feature113</td>\n",
       "      <td>['ip_city', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>feature114</td>\n",
       "      <td>['resource_owner', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>feature115</td>\n",
       "      <td>['resource_owner', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>feature116</td>\n",
       "      <td>['resource_owner', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>feature117</td>\n",
       "      <td>['resource_owner', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>feature118</td>\n",
       "      <td>['resource_type', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>feature119</td>\n",
       "      <td>['resource_type', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>feature120</td>\n",
       "      <td>['resource_type', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>feature121</td>\n",
       "      <td>['resource_type', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>feature122</td>\n",
       "      <td>['resource_category', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>feature123</td>\n",
       "      <td>['resource_category', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>feature124</td>\n",
       "      <td>['resource_category', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>feature125</td>\n",
       "      <td>['resource_category', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>index</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0                                      Feature_combination  \\\n",
       "0      feature1                                       ['time_stamp_day']   \n",
       "1      feature2                                      ['time_stamp_hour']   \n",
       "2      feature3                                     ['time_stamp_3hour']   \n",
       "3      feature4                                     ['time_stamp_6hour']   \n",
       "4      feature5                                       ['time_stamp_day']   \n",
       "5      feature6                                      ['time_stamp_hour']   \n",
       "6      feature7                                     ['time_stamp_3hour']   \n",
       "7      feature8                                     ['time_stamp_6hour']   \n",
       "8      feature9                                       ['time_stamp_day']   \n",
       "9     feature10                                      ['time_stamp_hour']   \n",
       "10    feature11                                     ['time_stamp_3hour']   \n",
       "11    feature12                                     ['time_stamp_6hour']   \n",
       "12    feature13                                       ['time_stamp_day']   \n",
       "13    feature14                                      ['time_stamp_hour']   \n",
       "14    feature15                                     ['time_stamp_3hour']   \n",
       "15    feature16                                     ['time_stamp_6hour']   \n",
       "16    feature17                                       ['time_stamp_day']   \n",
       "17    feature18                                      ['time_stamp_hour']   \n",
       "18    feature19                                     ['time_stamp_3hour']   \n",
       "19    feature20                                     ['time_stamp_6hour']   \n",
       "20    feature21                                       ['time_stamp_day']   \n",
       "21    feature22                                      ['time_stamp_hour']   \n",
       "22    feature23                                     ['time_stamp_3hour']   \n",
       "23    feature24                                     ['time_stamp_6hour']   \n",
       "24    feature25                                       ['time_stamp_day']   \n",
       "25    feature26                                      ['time_stamp_hour']   \n",
       "26    feature27                                     ['time_stamp_3hour']   \n",
       "27    feature28                                     ['time_stamp_6hour']   \n",
       "28    feature29                                       ['time_stamp_day']   \n",
       "29    feature30                                      ['time_stamp_hour']   \n",
       "30    feature31                                     ['time_stamp_3hour']   \n",
       "31    feature32                                     ['time_stamp_6hour']   \n",
       "32    feature33                                       ['time_stamp_day']   \n",
       "33    feature34                                      ['time_stamp_hour']   \n",
       "34    feature35                                     ['time_stamp_3hour']   \n",
       "35    feature36                                     ['time_stamp_6hour']   \n",
       "36    feature37                                       ['time_stamp_day']   \n",
       "37    feature38                                      ['time_stamp_hour']   \n",
       "38    feature39                                     ['time_stamp_3hour']   \n",
       "39    feature40                                     ['time_stamp_6hour']   \n",
       "40    feature41                                           ['event_type']   \n",
       "41    feature42                                       ['time_stamp_day']   \n",
       "42    feature43                                      ['time_stamp_hour']   \n",
       "43    feature44                                     ['time_stamp_3hour']   \n",
       "44    feature45                                     ['time_stamp_6hour']   \n",
       "45    feature46                         ['user_agent', 'time_stamp_day']   \n",
       "46    feature47                        ['user_agent', 'time_stamp_hour']   \n",
       "47    feature48                       ['user_agent', 'time_stamp_3hour']   \n",
       "48    feature49                       ['user_agent', 'time_stamp_6hour']   \n",
       "49    feature50                         ['os_version', 'time_stamp_day']   \n",
       "50    feature51                        ['os_version', 'time_stamp_hour']   \n",
       "51    feature52                       ['os_version', 'time_stamp_3hour']   \n",
       "52    feature53                       ['os_version', 'time_stamp_6hour']   \n",
       "53    feature54                               ['ip_1', 'time_stamp_day']   \n",
       "54    feature55                              ['ip_1', 'time_stamp_hour']   \n",
       "55    feature56                             ['ip_1', 'time_stamp_3hour']   \n",
       "56    feature57                             ['ip_1', 'time_stamp_6hour']   \n",
       "57    feature58                              ['ip_12', 'time_stamp_day']   \n",
       "58    feature59                             ['ip_12', 'time_stamp_hour']   \n",
       "59    feature60                            ['ip_12', 'time_stamp_3hour']   \n",
       "60    feature61                            ['ip_12', 'time_stamp_6hour']   \n",
       "61    feature62                             ['ip_123', 'time_stamp_day']   \n",
       "62    feature63                            ['ip_123', 'time_stamp_hour']   \n",
       "63    feature64                           ['ip_123', 'time_stamp_3hour']   \n",
       "64    feature65                           ['ip_123', 'time_stamp_6hour']   \n",
       "65    feature66                            ['ip_1234', 'time_stamp_day']   \n",
       "66    feature67                           ['ip_1234', 'time_stamp_hour']   \n",
       "67    feature68                          ['ip_1234', 'time_stamp_3hour']   \n",
       "68    feature69                          ['ip_1234', 'time_stamp_6hour']   \n",
       "69    feature70                            ['ip_city', 'time_stamp_day']   \n",
       "70    feature71                           ['ip_city', 'time_stamp_hour']   \n",
       "71    feature72                          ['ip_city', 'time_stamp_3hour']   \n",
       "72    feature73                          ['ip_city', 'time_stamp_6hour']   \n",
       "73    feature74                     ['resource_owner', 'time_stamp_day']   \n",
       "74    feature75                    ['resource_owner', 'time_stamp_hour']   \n",
       "75    feature76                   ['resource_owner', 'time_stamp_3hour']   \n",
       "76    feature77                   ['resource_owner', 'time_stamp_6hour']   \n",
       "77    feature78                      ['resource_type', 'time_stamp_day']   \n",
       "78    feature79                     ['resource_type', 'time_stamp_hour']   \n",
       "79    feature80                    ['resource_type', 'time_stamp_3hour']   \n",
       "80    feature81                    ['resource_type', 'time_stamp_6hour']   \n",
       "81    feature82                  ['resource_category', 'time_stamp_day']   \n",
       "82    feature83                 ['resource_category', 'time_stamp_hour']   \n",
       "83    feature84                ['resource_category', 'time_stamp_3hour']   \n",
       "84    feature85                ['resource_category', 'time_stamp_6hour']   \n",
       "85    feature86           ['user_agent', 'time_stamp_day', 'event_type']   \n",
       "86    feature87          ['user_agent', 'time_stamp_hour', 'event_type']   \n",
       "87    feature88         ['user_agent', 'time_stamp_3hour', 'event_type']   \n",
       "88    feature89         ['user_agent', 'time_stamp_6hour', 'event_type']   \n",
       "89    feature90           ['os_version', 'time_stamp_day', 'event_type']   \n",
       "90    feature91          ['os_version', 'time_stamp_hour', 'event_type']   \n",
       "91    feature92         ['os_version', 'time_stamp_3hour', 'event_type']   \n",
       "92    feature93         ['os_version', 'time_stamp_6hour', 'event_type']   \n",
       "93    feature94                 ['ip_1', 'time_stamp_day', 'event_type']   \n",
       "94    feature95                ['ip_1', 'time_stamp_hour', 'event_type']   \n",
       "95    feature96               ['ip_1', 'time_stamp_3hour', 'event_type']   \n",
       "96    feature97               ['ip_1', 'time_stamp_6hour', 'event_type']   \n",
       "97    feature98                ['ip_12', 'time_stamp_day', 'event_type']   \n",
       "98    feature99               ['ip_12', 'time_stamp_hour', 'event_type']   \n",
       "99   feature100              ['ip_12', 'time_stamp_3hour', 'event_type']   \n",
       "100  feature101              ['ip_12', 'time_stamp_6hour', 'event_type']   \n",
       "101  feature102               ['ip_123', 'time_stamp_day', 'event_type']   \n",
       "102  feature103              ['ip_123', 'time_stamp_hour', 'event_type']   \n",
       "103  feature104             ['ip_123', 'time_stamp_3hour', 'event_type']   \n",
       "104  feature105             ['ip_123', 'time_stamp_6hour', 'event_type']   \n",
       "105  feature106              ['ip_1234', 'time_stamp_day', 'event_type']   \n",
       "106  feature107             ['ip_1234', 'time_stamp_hour', 'event_type']   \n",
       "107  feature108            ['ip_1234', 'time_stamp_3hour', 'event_type']   \n",
       "108  feature109            ['ip_1234', 'time_stamp_6hour', 'event_type']   \n",
       "109  feature110              ['ip_city', 'time_stamp_day', 'event_type']   \n",
       "110  feature111             ['ip_city', 'time_stamp_hour', 'event_type']   \n",
       "111  feature112            ['ip_city', 'time_stamp_3hour', 'event_type']   \n",
       "112  feature113            ['ip_city', 'time_stamp_6hour', 'event_type']   \n",
       "113  feature114       ['resource_owner', 'time_stamp_day', 'event_type']   \n",
       "114  feature115      ['resource_owner', 'time_stamp_hour', 'event_type']   \n",
       "115  feature116     ['resource_owner', 'time_stamp_3hour', 'event_type']   \n",
       "116  feature117     ['resource_owner', 'time_stamp_6hour', 'event_type']   \n",
       "117  feature118        ['resource_type', 'time_stamp_day', 'event_type']   \n",
       "118  feature119       ['resource_type', 'time_stamp_hour', 'event_type']   \n",
       "119  feature120      ['resource_type', 'time_stamp_3hour', 'event_type']   \n",
       "120  feature121      ['resource_type', 'time_stamp_6hour', 'event_type']   \n",
       "121  feature122    ['resource_category', 'time_stamp_day', 'event_type']   \n",
       "122  feature123   ['resource_category', 'time_stamp_hour', 'event_type']   \n",
       "123  feature124  ['resource_category', 'time_stamp_3hour', 'event_type']   \n",
       "124  feature125  ['resource_category', 'time_stamp_6hour', 'event_type']   \n",
       "\n",
       "              Standard     Poly  \n",
       "0           user_agent  nunique  \n",
       "1           user_agent  nunique  \n",
       "2           user_agent  nunique  \n",
       "3           user_agent  nunique  \n",
       "4           os_version  nunique  \n",
       "5           os_version  nunique  \n",
       "6           os_version  nunique  \n",
       "7           os_version  nunique  \n",
       "8                 ip_1  nunique  \n",
       "9                 ip_1  nunique  \n",
       "10                ip_1  nunique  \n",
       "11                ip_1  nunique  \n",
       "12               ip_12  nunique  \n",
       "13               ip_12  nunique  \n",
       "14               ip_12  nunique  \n",
       "15               ip_12  nunique  \n",
       "16              ip_123  nunique  \n",
       "17              ip_123  nunique  \n",
       "18              ip_123  nunique  \n",
       "19              ip_123  nunique  \n",
       "20             ip_1234  nunique  \n",
       "21             ip_1234  nunique  \n",
       "22             ip_1234  nunique  \n",
       "23             ip_1234  nunique  \n",
       "24             ip_city  nunique  \n",
       "25             ip_city  nunique  \n",
       "26             ip_city  nunique  \n",
       "27             ip_city  nunique  \n",
       "28      resource_owner  nunique  \n",
       "29      resource_owner  nunique  \n",
       "30      resource_owner  nunique  \n",
       "31      resource_owner  nunique  \n",
       "32       resource_type  nunique  \n",
       "33       resource_type  nunique  \n",
       "34       resource_type  nunique  \n",
       "35       resource_type  nunique  \n",
       "36   resource_category  nunique  \n",
       "37   resource_category  nunique  \n",
       "38   resource_category  nunique  \n",
       "39   resource_category  nunique  \n",
       "40               index    count  \n",
       "41               index    count  \n",
       "42               index    count  \n",
       "43               index    count  \n",
       "44               index    count  \n",
       "45               index    count  \n",
       "46               index    count  \n",
       "47               index    count  \n",
       "48               index    count  \n",
       "49               index    count  \n",
       "50               index    count  \n",
       "51               index    count  \n",
       "52               index    count  \n",
       "53               index    count  \n",
       "54               index    count  \n",
       "55               index    count  \n",
       "56               index    count  \n",
       "57               index    count  \n",
       "58               index    count  \n",
       "59               index    count  \n",
       "60               index    count  \n",
       "61               index    count  \n",
       "62               index    count  \n",
       "63               index    count  \n",
       "64               index    count  \n",
       "65               index    count  \n",
       "66               index    count  \n",
       "67               index    count  \n",
       "68               index    count  \n",
       "69               index    count  \n",
       "70               index    count  \n",
       "71               index    count  \n",
       "72               index    count  \n",
       "73               index    count  \n",
       "74               index    count  \n",
       "75               index    count  \n",
       "76               index    count  \n",
       "77               index    count  \n",
       "78               index    count  \n",
       "79               index    count  \n",
       "80               index    count  \n",
       "81               index    count  \n",
       "82               index    count  \n",
       "83               index    count  \n",
       "84               index    count  \n",
       "85               index    count  \n",
       "86               index    count  \n",
       "87               index    count  \n",
       "88               index    count  \n",
       "89               index    count  \n",
       "90               index    count  \n",
       "91               index    count  \n",
       "92               index    count  \n",
       "93               index    count  \n",
       "94               index    count  \n",
       "95               index    count  \n",
       "96               index    count  \n",
       "97               index    count  \n",
       "98               index    count  \n",
       "99               index    count  \n",
       "100              index    count  \n",
       "101              index    count  \n",
       "102              index    count  \n",
       "103              index    count  \n",
       "104              index    count  \n",
       "105              index    count  \n",
       "106              index    count  \n",
       "107              index    count  \n",
       "108              index    count  \n",
       "109              index    count  \n",
       "110              index    count  \n",
       "111              index    count  \n",
       "112              index    count  \n",
       "113              index    count  \n",
       "114              index    count  \n",
       "115              index    count  \n",
       "116              index    count  \n",
       "117              index    count  \n",
       "118              index    count  \n",
       "119              index    count  \n",
       "120              index    count  \n",
       "121              index    count  \n",
       "122              index    count  \n",
       "123              index    count  \n",
       "124              index    count  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('max_row',200) \n",
    "pd.set_option('display.max_colwidth', 100)\n",
    "pd.read_csv(\"/data/jupyter_root/dcube_data/no_name/feature_list.csv\",sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Feature_combination</th>\n",
       "      <th>Standard</th>\n",
       "      <th>Poly</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>feature126</td>\n",
       "      <td>['user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>feature127</td>\n",
       "      <td>['user_agent', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>feature128</td>\n",
       "      <td>['user_agent', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>feature129</td>\n",
       "      <td>['user_agent', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>feature130</td>\n",
       "      <td>['user_agent', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>feature131</td>\n",
       "      <td>['os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>feature132</td>\n",
       "      <td>['os_version', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>feature133</td>\n",
       "      <td>['os_version', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>feature134</td>\n",
       "      <td>['os_version', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>feature135</td>\n",
       "      <td>['os_version', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>feature136</td>\n",
       "      <td>['resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>feature137</td>\n",
       "      <td>['resource_owner', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>feature138</td>\n",
       "      <td>['resource_owner', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>feature139</td>\n",
       "      <td>['resource_owner', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>feature140</td>\n",
       "      <td>['resource_owner', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>feature141</td>\n",
       "      <td>['resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>feature142</td>\n",
       "      <td>['resource_type', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>feature143</td>\n",
       "      <td>['resource_type', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>feature144</td>\n",
       "      <td>['resource_type', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>feature145</td>\n",
       "      <td>['resource_type', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>feature146</td>\n",
       "      <td>['resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>feature147</td>\n",
       "      <td>['resource_category', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>feature148</td>\n",
       "      <td>['resource_category', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>feature149</td>\n",
       "      <td>['resource_category', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>feature150</td>\n",
       "      <td>['resource_category', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>feature151</td>\n",
       "      <td>['ip_1']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>feature152</td>\n",
       "      <td>['ip_1', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>feature153</td>\n",
       "      <td>['ip_1', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>feature154</td>\n",
       "      <td>['ip_1', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>feature155</td>\n",
       "      <td>['ip_1', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>feature156</td>\n",
       "      <td>['ip_12']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>feature157</td>\n",
       "      <td>['ip_12', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>feature158</td>\n",
       "      <td>['ip_12', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>feature159</td>\n",
       "      <td>['ip_12', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>feature160</td>\n",
       "      <td>['ip_12', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>feature161</td>\n",
       "      <td>['ip_123']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>feature162</td>\n",
       "      <td>['ip_123', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>feature163</td>\n",
       "      <td>['ip_123', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>feature164</td>\n",
       "      <td>['ip_123', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>feature165</td>\n",
       "      <td>['ip_123', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>feature166</td>\n",
       "      <td>['ip_1234']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>feature167</td>\n",
       "      <td>['ip_1234', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>feature168</td>\n",
       "      <td>['ip_1234', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>feature169</td>\n",
       "      <td>['ip_1234', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>feature170</td>\n",
       "      <td>['ip_1234', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>feature171</td>\n",
       "      <td>['ip_city']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>feature172</td>\n",
       "      <td>['ip_city', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>feature173</td>\n",
       "      <td>['ip_city', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>feature174</td>\n",
       "      <td>['ip_city', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>feature175</td>\n",
       "      <td>['ip_city', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>feature176</td>\n",
       "      <td>['os_version', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>feature177</td>\n",
       "      <td>['resource_owner', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>feature178</td>\n",
       "      <td>['resource_type', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>feature179</td>\n",
       "      <td>['resource_category', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>feature180</td>\n",
       "      <td>['ip_1', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>feature181</td>\n",
       "      <td>['ip_12', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>feature182</td>\n",
       "      <td>['ip_123', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>feature183</td>\n",
       "      <td>['ip_1234', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>feature184</td>\n",
       "      <td>['ip_city', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>feature185</td>\n",
       "      <td>['resource_owner', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>feature186</td>\n",
       "      <td>['resource_type', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>feature187</td>\n",
       "      <td>['resource_category', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>feature188</td>\n",
       "      <td>['ip_1', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>feature189</td>\n",
       "      <td>['ip_12', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>feature190</td>\n",
       "      <td>['ip_123', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>feature191</td>\n",
       "      <td>['ip_1234', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>feature192</td>\n",
       "      <td>['ip_city', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>feature193</td>\n",
       "      <td>['resource_type', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>feature194</td>\n",
       "      <td>['resource_category', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>feature195</td>\n",
       "      <td>['ip_1', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>feature196</td>\n",
       "      <td>['ip_12', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>feature197</td>\n",
       "      <td>['ip_123', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>feature198</td>\n",
       "      <td>['ip_1234', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>feature199</td>\n",
       "      <td>['ip_city', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>feature200</td>\n",
       "      <td>['resource_category', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>feature201</td>\n",
       "      <td>['ip_1', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>feature202</td>\n",
       "      <td>['ip_12', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>feature203</td>\n",
       "      <td>['ip_123', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>feature204</td>\n",
       "      <td>['ip_1234', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>feature205</td>\n",
       "      <td>['ip_city', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>feature206</td>\n",
       "      <td>['ip_1', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>feature207</td>\n",
       "      <td>['ip_12', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>feature208</td>\n",
       "      <td>['ip_123', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>feature209</td>\n",
       "      <td>['ip_1234', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>feature210</td>\n",
       "      <td>['ip_city', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>feature211</td>\n",
       "      <td>['user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>feature212</td>\n",
       "      <td>['user_agent', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>feature213</td>\n",
       "      <td>['user_agent', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>feature214</td>\n",
       "      <td>['user_agent', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>feature215</td>\n",
       "      <td>['user_agent', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>feature216</td>\n",
       "      <td>['os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>feature217</td>\n",
       "      <td>['os_version', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>feature218</td>\n",
       "      <td>['os_version', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>feature219</td>\n",
       "      <td>['os_version', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>feature220</td>\n",
       "      <td>['os_version', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>feature221</td>\n",
       "      <td>['resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>feature222</td>\n",
       "      <td>['resource_owner', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>feature223</td>\n",
       "      <td>['resource_owner', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>feature224</td>\n",
       "      <td>['resource_owner', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>feature225</td>\n",
       "      <td>['resource_owner', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>feature241</td>\n",
       "      <td>['ip_12']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>feature242</td>\n",
       "      <td>['ip_12', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>feature243</td>\n",
       "      <td>['ip_12', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>feature244</td>\n",
       "      <td>['ip_12', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>feature245</td>\n",
       "      <td>['ip_12', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>feature246</td>\n",
       "      <td>['ip_123']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>feature247</td>\n",
       "      <td>['ip_123', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>feature248</td>\n",
       "      <td>['ip_123', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>feature249</td>\n",
       "      <td>['ip_123', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>feature250</td>\n",
       "      <td>['ip_123', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>feature251</td>\n",
       "      <td>['ip_1234']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>feature252</td>\n",
       "      <td>['ip_1234', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>feature253</td>\n",
       "      <td>['ip_1234', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>feature254</td>\n",
       "      <td>['ip_1234', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>feature255</td>\n",
       "      <td>['ip_1234', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>feature256</td>\n",
       "      <td>['ip_city']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>feature257</td>\n",
       "      <td>['ip_city', 'time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>feature258</td>\n",
       "      <td>['ip_city', 'time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>feature259</td>\n",
       "      <td>['ip_city', 'time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>feature260</td>\n",
       "      <td>['ip_city', 'time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>feature261</td>\n",
       "      <td>['os_version', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>feature262</td>\n",
       "      <td>['resource_owner', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>feature263</td>\n",
       "      <td>['resource_type', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>feature264</td>\n",
       "      <td>['resource_category', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>feature265</td>\n",
       "      <td>['ip_1', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>feature266</td>\n",
       "      <td>['ip_12', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>feature267</td>\n",
       "      <td>['ip_123', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>feature268</td>\n",
       "      <td>['ip_1234', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>feature269</td>\n",
       "      <td>['ip_city', 'user_agent']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>feature270</td>\n",
       "      <td>['resource_owner', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>feature271</td>\n",
       "      <td>['resource_type', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>feature272</td>\n",
       "      <td>['resource_category', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>feature273</td>\n",
       "      <td>['ip_1', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>feature274</td>\n",
       "      <td>['ip_12', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>feature275</td>\n",
       "      <td>['ip_123', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>feature276</td>\n",
       "      <td>['ip_1234', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>feature277</td>\n",
       "      <td>['ip_city', 'os_version']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>feature278</td>\n",
       "      <td>['resource_type', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>feature279</td>\n",
       "      <td>['resource_category', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>feature280</td>\n",
       "      <td>['ip_1', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>feature281</td>\n",
       "      <td>['ip_12', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>feature282</td>\n",
       "      <td>['ip_123', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>feature283</td>\n",
       "      <td>['ip_1234', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>feature284</td>\n",
       "      <td>['ip_city', 'resource_owner']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>feature285</td>\n",
       "      <td>['resource_category', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>feature286</td>\n",
       "      <td>['ip_1', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>feature287</td>\n",
       "      <td>['ip_12', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>feature288</td>\n",
       "      <td>['ip_123', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>feature289</td>\n",
       "      <td>['ip_1234', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>feature290</td>\n",
       "      <td>['ip_city', 'resource_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>feature291</td>\n",
       "      <td>['ip_1', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>feature292</td>\n",
       "      <td>['ip_12', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>feature293</td>\n",
       "      <td>['ip_123', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>feature294</td>\n",
       "      <td>['ip_1234', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>feature295</td>\n",
       "      <td>['ip_city', 'resource_category']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>count</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>feature296</td>\n",
       "      <td>['event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>feature297</td>\n",
       "      <td>['time_stamp_day']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>feature298</td>\n",
       "      <td>['time_stamp_hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>feature299</td>\n",
       "      <td>['time_stamp_3hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>feature300</td>\n",
       "      <td>['time_stamp_6hour']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>feature301</td>\n",
       "      <td>['user_agent', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>feature302</td>\n",
       "      <td>['user_agent', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>feature303</td>\n",
       "      <td>['user_agent', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>feature304</td>\n",
       "      <td>['user_agent', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>feature305</td>\n",
       "      <td>['os_version', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>feature306</td>\n",
       "      <td>['os_version', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>feature307</td>\n",
       "      <td>['os_version', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>feature308</td>\n",
       "      <td>['os_version', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>feature309</td>\n",
       "      <td>['resource_owner', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>feature310</td>\n",
       "      <td>['resource_owner', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>feature311</td>\n",
       "      <td>['resource_owner', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>feature312</td>\n",
       "      <td>['resource_owner', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>feature313</td>\n",
       "      <td>['resource_type', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>feature314</td>\n",
       "      <td>['resource_type', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>feature315</td>\n",
       "      <td>['resource_type', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>feature316</td>\n",
       "      <td>['resource_type', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>feature317</td>\n",
       "      <td>['resource_category', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>feature318</td>\n",
       "      <td>['resource_category', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>feature319</td>\n",
       "      <td>['resource_category', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>feature320</td>\n",
       "      <td>['resource_category', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>feature321</td>\n",
       "      <td>['ip_1', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>feature322</td>\n",
       "      <td>['ip_1', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>feature323</td>\n",
       "      <td>['ip_1', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>feature324</td>\n",
       "      <td>['ip_1', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>feature325</td>\n",
       "      <td>['ip_12', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>feature326</td>\n",
       "      <td>['ip_12', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>feature327</td>\n",
       "      <td>['ip_12', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>feature328</td>\n",
       "      <td>['ip_12', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>feature329</td>\n",
       "      <td>['ip_123', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>feature330</td>\n",
       "      <td>['ip_123', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>feature331</td>\n",
       "      <td>['ip_123', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>feature332</td>\n",
       "      <td>['ip_123', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>feature333</td>\n",
       "      <td>['ip_1234', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>feature334</td>\n",
       "      <td>['ip_1234', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>feature335</td>\n",
       "      <td>['ip_1234', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>feature336</td>\n",
       "      <td>['ip_1234', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>feature337</td>\n",
       "      <td>['ip_city', 'time_stamp_day', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>feature338</td>\n",
       "      <td>['ip_city', 'time_stamp_hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>feature339</td>\n",
       "      <td>['ip_city', 'time_stamp_3hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>feature340</td>\n",
       "      <td>['ip_city', 'time_stamp_6hour', 'event_type']</td>\n",
       "      <td>user_name</td>\n",
       "      <td>nunique</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>215 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0                            Feature_combination   Standard  \\\n",
       "0    feature126                                 ['user_agent']  user_name   \n",
       "1    feature127               ['user_agent', 'time_stamp_day']  user_name   \n",
       "2    feature128              ['user_agent', 'time_stamp_hour']  user_name   \n",
       "3    feature129             ['user_agent', 'time_stamp_3hour']  user_name   \n",
       "4    feature130             ['user_agent', 'time_stamp_6hour']  user_name   \n",
       "..          ...                                            ...        ...   \n",
       "210  feature336  ['ip_1234', 'time_stamp_6hour', 'event_type']  user_name   \n",
       "211  feature337    ['ip_city', 'time_stamp_day', 'event_type']  user_name   \n",
       "212  feature338   ['ip_city', 'time_stamp_hour', 'event_type']  user_name   \n",
       "213  feature339  ['ip_city', 'time_stamp_3hour', 'event_type']  user_name   \n",
       "214  feature340  ['ip_city', 'time_stamp_6hour', 'event_type']  user_name   \n",
       "\n",
       "        Poly  \n",
       "0    nunique  \n",
       "1    nunique  \n",
       "2    nunique  \n",
       "3    nunique  \n",
       "4    nunique  \n",
       "..       ...  \n",
       "210  nunique  \n",
       "211  nunique  \n",
       "212  nunique  \n",
       "213  nunique  \n",
       "214  nunique  \n",
       "\n",
       "[215 rows x 4 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('max_row',200) \n",
    "pd.set_option('display.max_colwidth', 100)\n",
    "pd.read_csv(\"/data/jupyter_root/dcube_data/no_name_add/feature_list.csv\",sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature_user</th>\n",
       "      <th>block_1.tuples</th>\n",
       "      <th>block_2.tuples</th>\n",
       "      <th>block_3.tuples</th>\n",
       "      <th>block_4.tuples</th>\n",
       "      <th>block_5.tuples</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 245766, 1597450, 319501, 1310734, 221217, 65569, 548900, 1130535, 41012, 1589314, 2212...</td>\n",
       "      <td>{1130498, 466948, 286725, 245766, 319501, 81934, 1310734, 1327123, 516120, 221211, 65569, 548900...</td>\n",
       "      <td>{1130498, 1089538, 466949, 499719, 1310734, 1646615, 65569, 1130535, 1089592, 114747, 1638472, 1...</td>\n",
       "      <td>{466948, 1658884, 546826, 1601547, 1310734, 1548306, 1529874, 118805, 1343510, 544789, 221211, 1...</td>\n",
       "      <td>{1595392, 1089538, 1658884, 245766, 499719, 221192, 348169, 546826, 141325, 1433614, 1556496, 12...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{20487, 221192, 1514503, 1182730, 76304, 1165329, 1548306, 282649, 521755, 1590812, 160289, 2207...</td>\n",
       "      <td>{280576, 373249, 389632, 102914, 395264, 160268, 319501, 1652756, 520214, 73243, 65569, 1583652,...</td>\n",
       "      <td>{198656, 73218, 117763, 114182, 1604102, 92681, 1573897, 1464845, 1290254, 453138, 1653782, 5207...</td>\n",
       "      <td>{1508352, 461314, 1343494, 245766, 118796, 1464845, 1313814, 471065, 73243, 250396, 118817, 6556...</td>\n",
       "      <td>{1576450, 1090563, 419333, 116742, 519687, 1524743, 118805, 116761, 542748, 475676, 366110, 2150...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{280576, 395264, 317450, 319501, 81934, 1308689, 1327123, 1652756, 118805, 520214, 1656859, 6556...</td>\n",
       "      <td>{1343494, 1536007, 245766, 1597450, 118796, 319501, 118805, 471065, 1607712, 118817, 65569, 5489...</td>\n",
       "      <td>{245766, 20487, 221192, 1165329, 1548306, 282649, 116788, 1071162, 520253, 1656894, 1052743, 577...</td>\n",
       "      <td>{116742, 1323024, 118805, 1646615, 116761, 542748, 1587229, 215072, 1634346, 479275, 550958, 107...</td>\n",
       "      <td>{198656, 245766, 1290254, 1298455, 215072, 460840, 1177644, 116788, 471108, 71753, 397389, 13067...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{280576, 1650688, 395264, 286725, 317450, 319501, 81934, 1308689, 1327123, 1652756, 118805, 5202...</td>\n",
       "      <td>{1595392, 243714, 1644547, 466948, 102406, 499719, 546826, 419854, 1290254, 1556498, 1327123, 52...</td>\n",
       "      <td>{1343494, 1536007, 245766, 317450, 1597450, 118796, 319501, 118805, 471065, 503836, 1607712, 118...</td>\n",
       "      <td>{1089538, 116742, 1323024, 118805, 1646615, 1595415, 116761, 542748, 1587229, 1585183, 282656, 2...</td>\n",
       "      <td>{1601547, 118805, 1343510, 544789, 102430, 1251361, 548900, 528420, 542765, 247858, 178232, 1308...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 245766, 1323028, 247832, 1308713, 1316907, 1212475, 348223, 471108, 1321029, 1052743, ...</td>\n",
       "      <td>{1343494, 245766, 1085451, 1316875, 1433614, 669711, 1323024, 1331217, 1310734, 1323028, 1333269...</td>\n",
       "      <td>{745476, 1343494, 1308689, 1327123, 563221, 1343510, 471065, 284700, 41012, 178232, 471108, 5776...</td>\n",
       "      <td>{1338373, 163336, 1540628, 1336853, 1326614, 1502744, 280095, 1212475, 1347137, 523330, 547399, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1089538, 466948, 221192, 1548306, 1343510, 1671197, 1089592, 1097784, 1597498, 41040, 1630303, ...</td>\n",
       "      <td>{1343494, 245766, 1323028, 247832, 1308713, 1316907, 1212475, 348223, 471108, 1321029, 1052743, ...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{745476, 1343494, 1316875, 1323024, 1308689, 1327123, 1323028, 1343510, 1337369, 471065, 284700,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1089538, 466948, 221192, 1310734, 1548306, 1343510, 1671197, 65569, 1097772, 1089592, 1597498, ...</td>\n",
       "      <td>{1343494, 245766, 1323028, 247832, 1308713, 1316907, 1212475, 348223, 471108, 1321029, 1052743, ...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671217, 1671221, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 1085451, 1316875, 1433614, 669711, 1323024, 1331217, 1310734, 1323028, 1333269, 134351...</td>\n",
       "      <td>{745476, 1343494, 1433614, 1310734, 1323024, 1308689, 1327123, 1323028, 1343510, 1337369, 471065...</td>\n",
       "      <td>{1343494, 1085451, 1316875, 1433614, 669711, 1323024, 1331217, 1310734, 1323028, 563221, 1333269...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{745476, 1343494, 245766, 1085451, 1316875, 1310734, 669711, 1323024, 1308689, 1331217, 1327123,...</td>\n",
       "      <td>{745476, 1343494, 245766, 1085451, 1316875, 1433614, 669711, 1323024, 1308689, 1331217, 1310734,...</td>\n",
       "      <td>{1329920, 1158401, 1204865, 155009, 1587845, 215301, 655113, 433163, 682766, 1325968, 1140500, 6...</td>\n",
       "      <td>{1565955, 498563, 1338373, 1614091, 682766, 1540628, 1343510, 196378, 474020, 1351337, 1328553, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1337216, 1204865, 1329035, 1286284, 1433614, 648975, 1325968, 1264283, 1311644, 654619, 1412382...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 65569, 65582, 1212475, 524351, 393281, 656...</td>\n",
       "      <td>{172546, 116742, 444809, 383246, 676496, 156567, 533914, 118814, 283943, 1541160, 1594539, 22199...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1339910, 163336, 1433614, 1087015, 140328, 52275, 41012, 1319481, 1624648, 1344587, 1306705, 13...</td>\n",
       "      <td>{1329920, 1158401, 1204865, 155009, 1587845, 215301, 655113, 433163, 682766, 1325968, 1140500, 6...</td>\n",
       "      <td>{1556480, 1130498, 1089538, 286725, 1343494, 245766, 221192, 466949, 1556494, 1204240, 1294353, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1660930, 1089538, 116742, 221192, 233489, 1343510, 1671197, 118814, 108576, 157734, 204839, 460...</td>\n",
       "      <td>{1337216, 1204865, 1329035, 1286284, 1433614, 648975, 1325968, 1264283, 1311644, 654619, 1412382...</td>\n",
       "      <td>{1339910, 163336, 433163, 317972, 1343510, 1087015, 140328, 52275, 41012, 1344587, 1251930, 1340...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 65598, 5243...</td>\n",
       "      <td>{1130498, 1089538, 466948, 286725, 499719, 221192, 1556488, 458762, 81934, 1433614, 1204240, 154...</td>\n",
       "      <td>{137218, 1089538, 116742, 221192, 458762, 546826, 1085451, 419854, 118800, 1593363, 1564693, 134...</td>\n",
       "      <td>{172546, 137735, 501255, 1180681, 419854, 405006, 1646094, 498705, 1548306, 1523217, 1307156, 10...</td>\n",
       "      <td>{428544, 172546, 116742, 92681, 1590812, 118814, 95774, 160289, 462371, 1629734, 1569832, 154116...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1660930, 1089538, 116742, 221192, 1658889, 546826, 419854, 1548306, 1343510, 1052699, 1671197, ...</td>\n",
       "      <td>{1524736, 428544, 172546, 343043, 1180162, 92681, 1085451, 277004, 1539595, 1646094, 171534, 348...</td>\n",
       "      <td>{1539844, 116742, 1286284, 222092, 383246, 1343252, 1358101, 156567, 770842, 533914, 1157662, 11...</td>\n",
       "      <td>{523105, 172546, 222274, 283943, 420744, 247400, 676496, 1171188, 613781, 533914, 94590}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1660930, 1089538, 116742, 221192, 233489, 165908, 1343510, 1052699, 546845, 118814, 1671197, 10...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 65598, 52435...</td>\n",
       "      <td>{1089538, 466948, 466949, 1343494, 499719, 221192, 1556488, 1597450, 245766, 81934, 221199, 1548...</td>\n",
       "      <td>{1556480, 466948, 286725, 245766, 499719, 221192, 466949, 81934, 1556495, 1204240, 516120, 54890...</td>\n",
       "      <td>{1130498, 1644547, 245766, 81934, 1593363, 165908, 118805, 1323028, 1505303, 116774, 204839, 235...</td>\n",
       "      <td>{461314, 1644547, 1522181, 1510408, 92681, 1303050, 498184, 160268, 1590285, 191499, 1523217, 15...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 65598, 52435...</td>\n",
       "      <td>{1089538, 466948, 466949, 1343494, 499719, 221192, 1556488, 1597450, 245766, 81934, 221199, 1548...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 1343510, 1671197, 65569, 32805, 65582, 1146929, 1671224, 65598, 524351, 393281, 65602,...</td>\n",
       "      <td>{466948, 1343494, 499719, 221192, 245766, 1556495, 1343510, 532517, 1130535, 1097770, 41012, 108...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 65598, 52435...</td>\n",
       "      <td>{1343494, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 65598, 5243...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 524...</td>\n",
       "      <td>{1556480, 1130498, 1089538, 466948, 286725, 1343494, 499719, 221192, 1556488, 1597450, 245766, 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 65598, 39328...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1556480, 1644547, 466948, 286725, 245766, 221192, 1658889, 546826, 81934, 419854, 1204240, 1308...</td>\n",
       "      <td>{1343494, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 65598, 524351, 393281, 65602,...</td>\n",
       "      <td>{1556480, 1130498, 466948, 286725, 245766, 221192, 1556488, 1597450, 81934, 221199, 1204240, 155...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1671224, 65598, 524351, 3932...</td>\n",
       "      <td>{1556480, 1130498, 1089538, 466948, 745476, 1343494, 499719, 221192, 1556488, 245766, 466949, 81...</td>\n",
       "      <td>{1660930, 745476, 286725, 499719, 1556488, 458762, 81934, 419854, 215055, 145423, 165908, 133326...</td>\n",
       "      <td>{1592193, 172546, 343043, 1568259, 1564545, 1130246, 1650444, 1594637, 471182, 405006, 1538318, ...</td>\n",
       "      <td>{308234, 1167883, 1590285, 292877, 334868, 1647648, 118305, 1649189, 425004, 398385, 1347123, 15...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1671224, 65598, 524351, 3932...</td>\n",
       "      <td>{1343494, 1671194, 1671197, 65569, 65582, 1671224, 65598, 524351, 393281, 65602, 1638472, 154016...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 1146929, 1671224, 65598, 524351, 39...</td>\n",
       "      <td>{1556480, 1130498, 1089538, 466948, 286725, 745476, 1343494, 221192, 1556488, 1597450, 245766, 4...</td>\n",
       "      <td>{1089538, 466948, 1343494, 499719, 221192, 1556488, 458762, 81934, 1433614, 1556495, 1548306, 13...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1671224, 65598, 524351, 393281, 1638...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1671224, 65598, 524351, 3932...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1146929, 1671224, 65598, 524...</td>\n",
       "      <td>{1556480, 1130498, 1089538, 466948, 745476, 1343494, 466949, 221192, 458762, 1597450, 81934, 155...</td>\n",
       "      <td>{1089538, 466948, 286725, 1343494, 245766, 221192, 458762, 1556495, 1204240, 1548306, 1564693, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1671224, 65598, 524351, 3932...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "      <td>{1556480, 1089538, 466948, 745476, 1343494, 499719, 221192, 1556488, 245766, 1433614, 1556495, 1...</td>\n",
       "      <td>{395264, 1595392, 466948, 745476, 1343494, 499719, 221192, 102406, 118796, 1556495, 1609744, 118...</td>\n",
       "      <td>{1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{198656, 317444, 1601547, 1052699, 65569, 1177644, 520253, 1564734, 1611845, 1302614, 118880, 11...</td>\n",
       "      <td>{320006, 116742, 1524742, 1182730, 277004, 1433614, 1523217, 1180181, 1540634, 1180187, 1637919,...</td>\n",
       "      <td>{198656, 320006, 1645581, 1180695, 1502744, 1100314, 118305, 1283108, 1654309, 1608230, 501292, ...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1089538, 245766, 499719, 221192, 81934, 1310734, 1548306, 1343510, 204822, 1671194, 221211, 167...</td>\n",
       "      <td>{198656, 1601547, 1433614, 1052699, 65569, 1177644, 520253, 1564734, 118880, 1650787, 1169517, 1...</td>\n",
       "      <td>{1089538, 286725, 245766, 499719, 221192, 466949, 1310734, 1204240, 1548306, 204822, 1671194, 65...</td>\n",
       "      <td>{137218, 626693, 1343494, 1323024, 448534, 1540121, 282653, 118814, 464929, 1052708, 1308712, 54...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1089538, 466948, 745476, 245766, 1556494, 1343510, 1671194, 1671197, 65569, 548900, 1589291, 10...</td>\n",
       "      <td>{1595904, 198656, 1520131, 317444, 601093, 1601547, 1180181, 1180695, 1502744, 1100314, 1180187,...</td>\n",
       "      <td>{1130498, 1089538, 466948, 245766, 221192, 1433614, 1310734, 1204240, 1556495, 1548306, 1556498,...</td>\n",
       "      <td>{1556480, 1089538, 466949, 1343494, 499719, 245766, 1597450, 319501, 81934, 1310734, 1327123, 16...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1089538, 466948, 1343494, 245766, 221192, 1597450, 319501, 1343510, 1671197, 65569, 548900, 204...</td>\n",
       "      <td>{198656, 317444, 116742, 1601547, 1052699, 65569, 1177644, 520253, 1564734, 1302614, 118880, 116...</td>\n",
       "      <td>{1089538, 466948, 245766, 1433614, 1556495, 204822, 221211, 548900, 532517, 1097770, 1097772, 14...</td>\n",
       "      <td>{1130498, 466949, 245766, 221192, 1556494, 1433614, 1204240, 1646615, 1597465, 1671197, 65569, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671197, 65569, 1146929, 1671217, 1671221, 1671224,...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1671194, 1671197, 65569, 32805, 65582, 1212475, 524351, 65602, 154017...</td>\n",
       "      <td>{1130498, 1089538, 466948, 466949, 245766, 499719, 1556488, 1556494, 1310734, 1556495, 1556498, ...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671197, 65569, 1146929, 1671217, 1671221, 1671224,...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1212475, 655...</td>\n",
       "      <td>{1130498, 1089538, 286725, 245766, 466949, 319501, 1556494, 1556495, 1548306, 1646615, 221208, 1...</td>\n",
       "      <td>{1658884, 221192, 1085451, 1556494, 1529874, 118805, 221211, 1671197, 118814, 548900, 544809, 16...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671197, 65569, 1146929, 1671217, 1671221, 1671224,...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1671221, 167...</td>\n",
       "      <td>{1089538, 466949, 245766, 1556495, 1097770, 1490992, 1097784, 114747, 1056832, 442446, 65614, 65...</td>\n",
       "      <td>{1650688, 116742, 77833, 215055, 1323024, 1529874, 118805, 221211, 1671197, 118814, 1251361, 544...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671197, 65569, 1146929, 1671217, 1671221, 1671224,...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1212475, 655...</td>\n",
       "      <td>{1089538, 499719, 1310734, 1556495, 1646628, 1097770, 1671221, 1056832, 221251, 1671238, 524359,...</td>\n",
       "      <td>{1556494, 1323024, 1331217, 1529874, 1327123, 118805, 221211, 1251361, 544809, 1089592, 1456197,...</td>\n",
       "      <td>{428544, 99123, 1671197}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 65569, 1671217, 1212475, 65598, 524351, 393281, 167...</td>\n",
       "      <td>{1089538, 245766, 221192, 1556488, 1597450, 319501, 1310734, 221199, 1556496, 1204240, 1548306, ...</td>\n",
       "      <td>{466948, 499719, 221192, 1548306, 1671197, 204839, 1130535, 1097772, 1490992, 1089592, 352314, 1...</td>\n",
       "      <td>{428544, 172546, 1610242, 116742, 92681, 1127453, 118814, 73255, 1541160, 1567280, 1300023, 3523...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671217, 16...</td>\n",
       "      <td>{1556480, 1089538, 466948, 499719, 221192, 458762, 1204240, 1548306, 1564693, 221208, 1540121, 1...</td>\n",
       "      <td>{137218, 1660930, 1089538, 282626, 116742, 1658889, 1085451, 1343510, 546845, 1671197, 157734, 1...</td>\n",
       "      <td>{428544, 116742, 118805, 1157662, 118814, 95774, 254502, 204839, 1541160, 352314, 1175114, 31854...</td>\n",
       "      <td>{420744, 247400}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671217, 16...</td>\n",
       "      <td>{1556480, 1089538, 466948, 499719, 221192, 458762, 1204240, 1548306, 1540121, 1597465, 1671197, ...</td>\n",
       "      <td>{1660930, 116742, 1658889, 118805, 1343510, 1671197, 118814, 204839, 1097772, 1089592, 352314, 3...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1660930, 1089538, 282626, 116742, 221192, 1658889, 1085451, 1609744, 233489, 1343510, 1052699, ...</td>\n",
       "      <td>{428544, 137218, 1170949, 137735, 501255, 1649671, 384010, 1523217, 118805, 1590812, 1671197, 11...</td>\n",
       "      <td>{428544, 116742, 1127453, 118814, 1541160, 1567280, 352314, 51782, 1175114, 1638988, 318541, 354...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671217, 16...</td>\n",
       "      <td>{1556480, 1089538, 466948, 499719, 221192, 458762, 1204240, 1548306, 1564693, 221208, 1540121, 1...</td>\n",
       "      <td>{137218, 1660930, 1089538, 282626, 116742, 1658889, 1085451, 1343510, 546845, 1671197, 157734, 1...</td>\n",
       "      <td>{428544, 1658889, 277004, 1646094, 171534, 1580054, 462371, 204839, 1515047, 1089592, 1074749, 1...</td>\n",
       "      <td>{428544, 1539844, 116742, 222092, 383246, 676496, 118805, 613781, 1666326, 1084693, 770842, 5339...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671217, 16...</td>\n",
       "      <td>{1556480, 1089538, 466948, 499719, 221192, 458762, 1204240, 1548306, 1540121, 1597465, 1671197, ...</td>\n",
       "      <td>{1660930, 116742, 1658889, 118805, 1343510, 1671197, 118814, 204839, 1097772, 1089592, 352314, 3...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1310734, 1343510, 65569, 65582, 1671221, 65598, 524351, 1671238, 524359, 1540168, 524364, 65614...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671221, 1...</td>\n",
       "      <td>{245766, 221192, 1433614, 65569, 1646628, 32805, 1302564, 204839, 139311, 1597498, 1056832, 1589...</td>\n",
       "      <td>{1635841, 73218, 1677315, 138242, 320006, 1097228, 1615376, 1165329, 1575447, 1505303, 1180187, ...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{458762, 1310734, 1343510, 65569, 65582, 1671221, 65598, 524351, 1671238, 524359, 1540168, 52436...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671221, 1...</td>\n",
       "      <td>{745476, 286725, 245766, 499719, 221192, 466949, 1556494, 1433614, 1310734, 1294353, 1556498, 15...</td>\n",
       "      <td>{458762, 1310734, 1343510, 32805, 65582, 1671221, 65598, 524359, 1638472, 65614, 1540176, 117974...</td>\n",
       "      <td>{1343494, 221192, 75789, 419854, 1159181, 1433614, 1593363, 116761, 1656859, 247836, 282653, 118...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{1310734, 1343510, 65569, 65582, 1671221, 65598, 524351, 1671238, 524359, 1540168, 524364, 65614...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671221, 1...</td>\n",
       "      <td>{210946, 481284, 116742, 102407, 221192, 348169, 317450, 546826, 1296396, 75789, 1433614, 215055...</td>\n",
       "      <td>{1556480, 499719, 319501, 1433614, 1204240, 1556498, 1327123, 1646615, 1597465, 221211, 65569, 3...</td>\n",
       "      <td>{1343494, 1556494, 1310734, 1294353, 1343510, 1646640, 1302579, 114747, 1302588, 524359, 286798,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "      <td>{458762, 1310734, 1343510, 65569, 65582, 1671221, 65598, 524351, 1671238, 524359, 1540168, 52436...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671221, 1...</td>\n",
       "      <td>{458762, 1310734, 1343510, 65569, 32805, 65582, 1671221, 65598, 524351, 1671238, 524359, 1638472...</td>\n",
       "      <td>{1343494, 221192, 1556488, 1433614, 221199, 1556496, 516120, 1540121, 1671194, 1671197, 548900, ...</td>\n",
       "      <td>{1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                           feature_user  \\\n",
       "0   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "1   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "2   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "3   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "4   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "5   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "6   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "7   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "8   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "9   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "10  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "11  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "12  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "13  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "14  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "15  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "16  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "17  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "18  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "19  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "20  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "21  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "22  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "23  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "24  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "25  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "26  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "27  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "28  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "29  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "30  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "31  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "32  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "33  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "34  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "35  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "36  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "37  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "38  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "39  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "40  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "41  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "42  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "43  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "44  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "\n",
       "                                                                                         block_1.tuples  \\\n",
       "0   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "1   {1343494, 245766, 1597450, 319501, 1310734, 221217, 65569, 548900, 1130535, 41012, 1589314, 2212...   \n",
       "2   {20487, 221192, 1514503, 1182730, 76304, 1165329, 1548306, 282649, 521755, 1590812, 160289, 2207...   \n",
       "3   {280576, 395264, 317450, 319501, 81934, 1308689, 1327123, 1652756, 118805, 520214, 1656859, 6556...   \n",
       "4   {280576, 1650688, 395264, 286725, 317450, 319501, 81934, 1308689, 1327123, 1652756, 118805, 5202...   \n",
       "5   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "6   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "7   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "8   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "9   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "10  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "11  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "12  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "13  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "14  {1343494, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 65598, 5243...   \n",
       "15  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "16  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "17  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 65598, 52435...   \n",
       "18  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 65598, 52435...   \n",
       "19  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 65598, 52435...   \n",
       "20  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 65598, 39328...   \n",
       "21  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1671224, 65598, 524351, 3932...   \n",
       "22  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1671224, 65598, 524351, 3932...   \n",
       "23  {1343494, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1671224, 65598, 524351, 393281, 1638...   \n",
       "24  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1671224, 65598, 524351, 3932...   \n",
       "25  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "26  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "27  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "28  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "29  {1343494, 458762, 1310734, 1343510, 1540121, 1671197, 65569, 1146929, 1671217, 1671221, 1671224,...   \n",
       "30  {1343494, 458762, 1310734, 1343510, 1540121, 1671197, 65569, 1146929, 1671217, 1671221, 1671224,...   \n",
       "31  {1343494, 458762, 1310734, 1343510, 1540121, 1671197, 65569, 1146929, 1671217, 1671221, 1671224,...   \n",
       "32  {1343494, 458762, 1310734, 1343510, 1540121, 1671197, 65569, 1146929, 1671217, 1671221, 1671224,...   \n",
       "33  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "34  {1343494, 458762, 1310734, 1343510, 1540121, 65569, 1671217, 1212475, 65598, 524351, 393281, 167...   \n",
       "35  {1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671217, 16...   \n",
       "36  {1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671217, 16...   \n",
       "37  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "38  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "39  {1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671217, 16...   \n",
       "40  {1343494, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671217, 16...   \n",
       "41  {1310734, 1343510, 65569, 65582, 1671221, 65598, 524351, 1671238, 524359, 1540168, 524364, 65614...   \n",
       "42  {458762, 1310734, 1343510, 65569, 65582, 1671221, 65598, 524351, 1671238, 524359, 1540168, 52436...   \n",
       "43  {1310734, 1343510, 65569, 65582, 1671221, 65598, 524351, 1671238, 524359, 1540168, 524364, 65614...   \n",
       "44  {458762, 1310734, 1343510, 65569, 65582, 1671221, 65598, 524351, 1671238, 524359, 1540168, 52436...   \n",
       "\n",
       "                                                                                         block_2.tuples  \\\n",
       "0   {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "1   {1130498, 466948, 286725, 245766, 319501, 81934, 1310734, 1327123, 516120, 221211, 65569, 548900...   \n",
       "2   {280576, 373249, 389632, 102914, 395264, 160268, 319501, 1652756, 520214, 73243, 65569, 1583652,...   \n",
       "3   {1343494, 1536007, 245766, 1597450, 118796, 319501, 118805, 471065, 1607712, 118817, 65569, 5489...   \n",
       "4   {1595392, 243714, 1644547, 466948, 102406, 499719, 546826, 419854, 1290254, 1556498, 1327123, 52...   \n",
       "5   {1343494, 245766, 1323028, 247832, 1308713, 1316907, 1212475, 348223, 471108, 1321029, 1052743, ...   \n",
       "6   {1089538, 466948, 221192, 1548306, 1343510, 1671197, 1089592, 1097784, 1597498, 41040, 1630303, ...   \n",
       "7   {1089538, 466948, 221192, 1310734, 1548306, 1343510, 1671197, 65569, 1097772, 1089592, 1597498, ...   \n",
       "8   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "9   {745476, 1343494, 245766, 1085451, 1316875, 1310734, 669711, 1323024, 1308689, 1331217, 1327123,...   \n",
       "10  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "11  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "12  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "13  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "14  {1130498, 1089538, 466948, 286725, 499719, 221192, 1556488, 458762, 81934, 1433614, 1204240, 154...   \n",
       "15  {1660930, 1089538, 116742, 221192, 1658889, 546826, 419854, 1548306, 1343510, 1052699, 1671197, ...   \n",
       "16  {1660930, 1089538, 116742, 221192, 233489, 165908, 1343510, 1052699, 546845, 118814, 1671197, 10...   \n",
       "17  {1089538, 466948, 466949, 1343494, 499719, 221192, 1556488, 1597450, 245766, 81934, 221199, 1548...   \n",
       "18  {1089538, 466948, 466949, 1343494, 499719, 221192, 1556488, 1597450, 245766, 81934, 221199, 1548...   \n",
       "19  {1343494, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 65598, 5243...   \n",
       "20  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "21  {1556480, 1130498, 1089538, 466948, 745476, 1343494, 499719, 221192, 1556488, 245766, 466949, 81...   \n",
       "22  {1343494, 1671194, 1671197, 65569, 65582, 1671224, 65598, 524351, 393281, 65602, 1638472, 154016...   \n",
       "23  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1671224, 65598, 524351, 3932...   \n",
       "24  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "25  {198656, 317444, 1601547, 1052699, 65569, 1177644, 520253, 1564734, 1611845, 1302614, 118880, 11...   \n",
       "26  {1089538, 245766, 499719, 221192, 81934, 1310734, 1548306, 1343510, 204822, 1671194, 221211, 167...   \n",
       "27  {1089538, 466948, 745476, 245766, 1556494, 1343510, 1671194, 1671197, 65569, 548900, 1589291, 10...   \n",
       "28  {1089538, 466948, 1343494, 245766, 221192, 1597450, 319501, 1343510, 1671197, 65569, 548900, 204...   \n",
       "29  {1343494, 458762, 1310734, 1671194, 1671197, 65569, 32805, 65582, 1212475, 524351, 65602, 154017...   \n",
       "30  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1212475, 655...   \n",
       "31  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1671221, 167...   \n",
       "32  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1212475, 655...   \n",
       "33  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "34  {1089538, 245766, 221192, 1556488, 1597450, 319501, 1310734, 221199, 1556496, 1204240, 1548306, ...   \n",
       "35  {1556480, 1089538, 466948, 499719, 221192, 458762, 1204240, 1548306, 1564693, 221208, 1540121, 1...   \n",
       "36  {1556480, 1089538, 466948, 499719, 221192, 458762, 1204240, 1548306, 1540121, 1597465, 1671197, ...   \n",
       "37  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "38  {1660930, 1089538, 282626, 116742, 221192, 1658889, 1085451, 1609744, 233489, 1343510, 1052699, ...   \n",
       "39  {1556480, 1089538, 466948, 499719, 221192, 458762, 1204240, 1548306, 1564693, 221208, 1540121, 1...   \n",
       "40  {1556480, 1089538, 466948, 499719, 221192, 458762, 1204240, 1548306, 1540121, 1597465, 1671197, ...   \n",
       "41  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671221, 1...   \n",
       "42  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671221, 1...   \n",
       "43  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671221, 1...   \n",
       "44  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 65582, 1146929, 1671221, 1...   \n",
       "\n",
       "                                                                                         block_3.tuples  \\\n",
       "0   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "1   {1130498, 1089538, 466949, 499719, 1310734, 1646615, 65569, 1130535, 1089592, 114747, 1638472, 1...   \n",
       "2   {198656, 73218, 117763, 114182, 1604102, 92681, 1573897, 1464845, 1290254, 453138, 1653782, 5207...   \n",
       "3   {245766, 20487, 221192, 1165329, 1548306, 282649, 116788, 1071162, 520253, 1656894, 1052743, 577...   \n",
       "4   {1343494, 1536007, 245766, 317450, 1597450, 118796, 319501, 118805, 471065, 503836, 1607712, 118...   \n",
       "5   {1343494, 245766, 1085451, 1316875, 1433614, 669711, 1323024, 1331217, 1310734, 1323028, 1333269...   \n",
       "6   {1343494, 245766, 1323028, 247832, 1308713, 1316907, 1212475, 348223, 471108, 1321029, 1052743, ...   \n",
       "7   {1343494, 245766, 1323028, 247832, 1308713, 1316907, 1212475, 348223, 471108, 1321029, 1052743, ...   \n",
       "8   {1343494, 1085451, 1316875, 1433614, 669711, 1323024, 1331217, 1310734, 1323028, 1333269, 134351...   \n",
       "9   {745476, 1343494, 245766, 1085451, 1316875, 1433614, 669711, 1323024, 1308689, 1331217, 1310734,...   \n",
       "10  {1337216, 1204865, 1329035, 1286284, 1433614, 648975, 1325968, 1264283, 1311644, 654619, 1412382...   \n",
       "11  {1339910, 163336, 1433614, 1087015, 140328, 52275, 41012, 1319481, 1624648, 1344587, 1306705, 13...   \n",
       "12  {1660930, 1089538, 116742, 221192, 233489, 1343510, 1671197, 118814, 108576, 157734, 204839, 460...   \n",
       "13  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "14  {137218, 1089538, 116742, 221192, 458762, 546826, 1085451, 419854, 118800, 1593363, 1564693, 134...   \n",
       "15  {1524736, 428544, 172546, 343043, 1180162, 92681, 1085451, 277004, 1539595, 1646094, 171534, 348...   \n",
       "16  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "17  {1556480, 466948, 286725, 245766, 499719, 221192, 466949, 81934, 1556495, 1204240, 516120, 54890...   \n",
       "18  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "19  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "20  {1556480, 1644547, 466948, 286725, 245766, 221192, 1658889, 546826, 81934, 419854, 1204240, 1308...   \n",
       "21  {1660930, 745476, 286725, 499719, 1556488, 458762, 81934, 419854, 215055, 145423, 165908, 133326...   \n",
       "22  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 1146929, 1671224, 65598, 524351, 39...   \n",
       "23  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 1146929, 1671224, 65598, 524...   \n",
       "24  {1556480, 1089538, 466948, 745476, 1343494, 499719, 221192, 1556488, 245766, 1433614, 1556495, 1...   \n",
       "25  {320006, 116742, 1524742, 1182730, 277004, 1433614, 1523217, 1180181, 1540634, 1180187, 1637919,...   \n",
       "26  {198656, 1601547, 1433614, 1052699, 65569, 1177644, 520253, 1564734, 118880, 1650787, 1169517, 1...   \n",
       "27  {1595904, 198656, 1520131, 317444, 601093, 1601547, 1180181, 1180695, 1502744, 1100314, 1180187,...   \n",
       "28  {198656, 317444, 116742, 1601547, 1052699, 65569, 1177644, 520253, 1564734, 1302614, 118880, 116...   \n",
       "29  {1130498, 1089538, 466948, 466949, 245766, 499719, 1556488, 1556494, 1310734, 1556495, 1556498, ...   \n",
       "30  {1130498, 1089538, 286725, 245766, 466949, 319501, 1556494, 1556495, 1548306, 1646615, 221208, 1...   \n",
       "31  {1089538, 466949, 245766, 1556495, 1097770, 1490992, 1097784, 114747, 1056832, 442446, 65614, 65...   \n",
       "32  {1089538, 499719, 1310734, 1556495, 1646628, 1097770, 1671221, 1056832, 221251, 1671238, 524359,...   \n",
       "33  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "34  {466948, 499719, 221192, 1548306, 1671197, 204839, 1130535, 1097772, 1490992, 1089592, 352314, 1...   \n",
       "35  {137218, 1660930, 1089538, 282626, 116742, 1658889, 1085451, 1343510, 546845, 1671197, 157734, 1...   \n",
       "36  {1660930, 116742, 1658889, 118805, 1343510, 1671197, 118814, 204839, 1097772, 1089592, 352314, 3...   \n",
       "37  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "38  {428544, 137218, 1170949, 137735, 501255, 1649671, 384010, 1523217, 118805, 1590812, 1671197, 11...   \n",
       "39  {137218, 1660930, 1089538, 282626, 116742, 1658889, 1085451, 1343510, 546845, 1671197, 157734, 1...   \n",
       "40  {1660930, 116742, 1658889, 118805, 1343510, 1671197, 118814, 204839, 1097772, 1089592, 352314, 3...   \n",
       "41  {245766, 221192, 1433614, 65569, 1646628, 32805, 1302564, 204839, 139311, 1597498, 1056832, 1589...   \n",
       "42  {745476, 286725, 245766, 499719, 221192, 466949, 1556494, 1433614, 1310734, 1294353, 1556498, 15...   \n",
       "43  {210946, 481284, 116742, 102407, 221192, 348169, 317450, 546826, 1296396, 75789, 1433614, 215055...   \n",
       "44  {458762, 1310734, 1343510, 65569, 32805, 65582, 1671221, 65598, 524351, 1671238, 524359, 1638472...   \n",
       "\n",
       "                                                                                         block_4.tuples  \\\n",
       "0   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "1   {466948, 1658884, 546826, 1601547, 1310734, 1548306, 1529874, 118805, 1343510, 544789, 221211, 1...   \n",
       "2   {1508352, 461314, 1343494, 245766, 118796, 1464845, 1313814, 471065, 73243, 250396, 118817, 6556...   \n",
       "3   {116742, 1323024, 118805, 1646615, 116761, 542748, 1587229, 215072, 1634346, 479275, 550958, 107...   \n",
       "4   {1089538, 116742, 1323024, 118805, 1646615, 1595415, 116761, 542748, 1587229, 1585183, 282656, 2...   \n",
       "5   {745476, 1343494, 1308689, 1327123, 563221, 1343510, 471065, 284700, 41012, 178232, 471108, 5776...   \n",
       "6   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "7   {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...   \n",
       "8   {745476, 1343494, 1433614, 1310734, 1323024, 1308689, 1327123, 1323028, 1343510, 1337369, 471065...   \n",
       "9   {1329920, 1158401, 1204865, 155009, 1587845, 215301, 655113, 433163, 682766, 1325968, 1140500, 6...   \n",
       "10  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 65569, 65582, 1212475, 524351, 393281, 656...   \n",
       "11  {1329920, 1158401, 1204865, 155009, 1587845, 215301, 655113, 433163, 682766, 1325968, 1140500, 6...   \n",
       "12  {1337216, 1204865, 1329035, 1286284, 1433614, 648975, 1325968, 1264283, 1311644, 654619, 1412382...   \n",
       "13  {1343494, 458762, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 1671224, 655...   \n",
       "14  {172546, 137735, 501255, 1180681, 419854, 405006, 1646094, 498705, 1548306, 1523217, 1307156, 10...   \n",
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       "32                                                                             {428544, 99123, 1671197}  \n",
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       "35                                                                                     {420744, 247400}  \n",
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       "43  {1343494, 1556494, 1310734, 1294353, 1343510, 1646640, 1302579, 114747, 1302588, 524359, 286798,...  \n",
       "44  {1343494, 458762, 1310734, 1343510, 1540121, 1671194, 1671197, 65569, 32805, 65582, 1146929, 167...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('max_row',200) \n",
    "pd.set_option('display.max_colwidth', 100)\n",
    "pd.read_csv(\"/data/jupyter_root/dcube_data/no_name_add/result_list2_811.csv\",sep=',')"
   ]
  }
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